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ECCV06(IV: 464-475).
Springer DOI
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CLOR06(207-224).
Springer DOI
0711
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Earlier: A1, A4, A2, A3:
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CIAP05(612-620).
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1307
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Earlier: A1, A2, A4, Only:
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Springer DOI
1011
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Dyn3D09(96-109).
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Springer DOI
1311
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Earlier: A1, A3, A2, A4:
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BMVC12(50).
DOI Link
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BibRef
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GCPR16(179-191).
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1611
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Selecting Influential Examples: Active Learning with Expected Model
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ECCV14(IV: 562-577).
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1702
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Freytag, A.[Alexander],
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GCPR13(282-291).
Springer DOI
1311
BibRef
Earlier:
Rapid Uncertainty Computation with Gaussian Processes and Histogram
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ACCV12(II:511-524).
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1304
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Freytag, A.[Alexander],
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ECCV12(IV: 85-98).
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1210
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CVIU(120), No. 1, 2014, pp. 81-90.
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1403
Computer vision
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Osuna-Enciso, V.[Valentín],
Bioinspired metaheuristics for image segmentation,
ELCVIA(13), No. 2, 2014, pp. xx-yy.
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CACM(57), No. 11, November 2014, pp. 68-77.
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JVCIR(28), No. 1, 2015, pp. 83-96.
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Analytical models
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CVPR13(3143-3150)
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1309
Explore effects by using humans in loop for parts of the problem.
BibRef
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Semantic segmentation
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Tung, F.[Frederick],
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CVIU(143), No. 1, 2016, pp. 191-200.
Elsevier DOI
1601
BibRef
Earlier:
CollageParsing:
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ECCV14(VI: 511-525).
Springer DOI
1408
Image parsing
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Zarchi, M.S.,
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Visual term. Image parsing.
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Diebold, J.[Julia],
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Midrange Geometric Interactions for Semantic Segmentation,
IJCV(117), No. 3, May 2016, pp. 199-225.
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1605
See also Convex Optimization for Scene Understanding.
See also Proximity Priors for Variational Semantic Segmentation and Recognition.
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Nieuwenhuis, C.[Claudia],
Strekalovskiy, E.[Evgeny],
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Proportion Priors for Image Sequence Segmentation,
ICCV13(2328-2335)
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1403
BibRef
Earlier: A2, A1, A3:
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ECCV12(VII: 208-221).
Springer DOI
1210
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Hazirbas, C.[Caner],
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Optimizing the Relevance-Redundancy Tradeoff for Efficient Semantic
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1506
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Zand, M.,
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Mustaffa, M.R.,
Ontology-Based Semantic Image Segmentation Using Mixture Models and
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1606
image segmentation
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IEEE DOI
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Detectors.
Image Segmentation; Object Candidates
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CVPR18(4233-4241)
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1812
Training, Task analysis, Visualization, Transfer functions,
Predictive models, Image segmentation, Genomics
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ECCV14(VII: 297-312).
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See also Indoor Scene Understanding with RGB-D Images: Bottom-up Segmentation, Object Detection and Semantic Segmentation.
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1208
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1502
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Marmanis, D.,
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PandRS(135), No. Supplement C, 2018, pp. 158-172.
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1712
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Zhang, J.[Jing],
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IET-IPR(12), No. 8, August 2018, pp. 1331-1337.
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1810
backpropagation, feature extraction, image classification,
image coding, local appearance features, contextual feature,
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Noormohamadi, N.[Neda],
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Ates, H.F.[Hasan F.],
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Image parsing, Segmentation, Superpixel, MRF
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Blott, G.[Gregor],
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Semantic Segmentation of Fisheye Images,
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1905
BibRef
Li, X.,
Ma, H.,
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Weaklier Supervised Semantic Segmentation With Only One Image Level
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IP(29), No. 1, 2020, pp. 128-141.
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1910
image recognition, image segmentation, object recognition,
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dual-branch iterative learning
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Song, Y.,
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Semi-Supervised Seq2seq Joint-Stochastic-Approximation Autoencoders
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2001
Semi-supervised learning, seq2seq, semantic parsing,
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Shimoda, W.[Wataru],
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Weakly supervised semantic segmentation using distinct class specific
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CVIU(191), 2020, pp. 102712.
Elsevier DOI
2002
BibRef
Earlier:
Distinct Class-Specific Saliency Maps for Weakly Supervised Semantic
Segmentation,
ECCV16(IV: 218-234).
Springer DOI
1611
Semantic segmentation, Weakly supervised learning,
Weakly supervised segmentation, Visualization, Deep learning
BibRef
Shimoda, W.[Wataru],
Yanai, K.[Keiji],
Self-Supervised Difference Detection for Weakly-Supervised Semantic
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ICCV19(5207-5216)
IEEE DOI
2004
estimation theory, image denoising, image segmentation,
iterative methods, learning (artificial intelligence),
Predictive models
BibRef
Yang, Z.E.[Zheng-Eng],
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Feng, M.T.[Ming-Tao],
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Sun, M.G.[Min-Gui],
Mao, Z.H.[Zhi-Hong],
Mian, A.[Ajmal],
Small Object Augmentation of Urban Scenes for Real-Time Semantic
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IP(29), 2020, pp. 5175-5190.
IEEE DOI
2004
For driving application.
Convolution, Image segmentation, Semantics, Real-time systems,
Standards, Training, Computational modeling, Semantic segmentation,
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Self-Supervised Model Adaptation for Multimodal Semantic Segmentation,
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Springer DOI
2005
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Mohan, R.[Rohit],
Valada, A.[Abhinav],
EfficientPS: Efficient Panoptic Segmentation,
IJCV(129), No. 5, May 2021, pp. 1551-1579.
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2105
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Wang, X.[Xiang],
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IJCV(128), No. 6, June 2020, pp. 1736-1749.
Springer DOI
2006
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Chen, Y.C.[Yun-Chun],
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Show, Match and Segment: Joint Weakly Supervised Learning of Semantic
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PAMI(43), No. 10, October 2021, pp. 3632-3647.
IEEE DOI
2109
Semantics, Task analysis, Image segmentation, Training, Clutter,
Proposals, Pattern matching, Semantic matching,
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Elsevier DOI
2008
Semantic segmentation, Loss function
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Seed picking crossover optimisation algorithm for semantic segmentation
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IET-IPR(14), No. 11, September 2020, pp. 2503-2511.
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IET-IPR(15), No. 13, November, pp. 3410-3410.
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Oric, M.[Marin],
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Efficient semantic segmentation with pyramidal fusion,
PR(110), 2021, pp. 107611.
Elsevier DOI
2011
Semantic segmentation, Real-time inference,
Shared resolution pyramid, Deep learning
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Lian, X.[Xuhang],
Pang, Y.W.[Yan-Wei],
Han, J.G.[Jun-Gong],
Pan, J.[Jing],
Cascaded hierarchical atrous spatial pyramid pooling module for
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PR(110), 2021, pp. 107622.
Elsevier DOI
2011
Semantic segmentation, Atrous convolution,
Atrous spatial pyramid pooling(ASPP), Cascaded module
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CVIU(202), 2021, pp. 103085.
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2012
Segmentation, X-ray, Mask R-CNN, Neural networks
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Choi, H.[Hyunguk],
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ADFNet:
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Zhang, Y.[Yifei],
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IVC(105), 2021, pp. 104042.
Elsevier DOI
2101
Survey, Semantic Segmentation. Image fusion, Multi-modal, Deep learning, Semantic segmentation
BibRef
Tasar, O.,
Giros, A.,
Tarabalka, Y.,
Alliez, P.,
Clerc, S.,
DAugNet: Unsupervised, Multisource, Multitarget, and Life-Long Domain
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GeoRS(59), No. 2, February 2021, pp. 1067-1081.
IEEE DOI
2101
Satellites, Training, Semantics, Image segmentation,
Adaptation models, Remote sensing, Standardization,
semantic segmentation
BibRef
Zhou, W.,
Wang, Y.,
Chu, J.,
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Bai, X.,
Xu, Y.,
Affinity Space Adaptation for Semantic Segmentation Across Domains,
IP(30), 2021, pp. 2549-2561.
IEEE DOI
2102
Semantics, Image segmentation, Cleaning, Annotations,
Adaptation models, Data models, Training,
affinity relationship
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Chan, L.[Lyndon],
Hosseini, M.S.[Mahdi S.],
Plataniotis, K.N.[Konstantinos N.],
A Comprehensive Analysis of Weakly-Supervised Semantic Segmentation in
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2102
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Huang, L.[Li],
He, M.L.[Mei-Ling],
Tan, C.[Chong],
Jiang, D.[Du],
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IET-IPR(14), No. 15, 15 December 2020, pp. 3689-3697.
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Zheng, Z.D.[Zhe-Dong],
Yang, Y.[Yi],
Rectifying Pseudo Label Learning via Uncertainty Estimation for Domain
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IJCV(129), No. 4, April 2021, pp. 1106-1120.
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2104
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Ji, J.[Jian],
Shi, R.[Rui],
Li, S.[Sitong],
Chen, P.[Peng],
Miao, Q.[Qiguang],
Encoder-Decoder With Cascaded CRFs for Semantic Segmentation,
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2105
BibRef
Yan, J.B.[Jie-Bin],
Zhong, Y.[Yu],
Fang, Y.M.[Yu-Ming],
Wang, Z.Y.[Zhang-Yang],
Ma, K.D.[Ke-De],
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Competition,
IJCV(129), No. 5, May 2021, pp. 1768-1786.
Springer DOI
2105
BibRef
Feng, Y.C.[Ying-Chao],
Sun, X.[Xian],
Diao, W.H.[Wen-Hui],
Li, J.[Jihao],
Gao, X.[Xin],
Double Similarity Distillation for Semantic Image Segmentation,
IP(30), 2021, pp. 5363-5376.
IEEE DOI
2106
Knowledge engineering, Image segmentation, Correlation, Semantics,
Task analysis, Complexity theory, Training,
convolutional neural networks
BibRef
Dong, G.S.[Gen-Shun],
Yan, Y.[Yan],
Shen, C.H.[Chun-Hua],
Wang, H.Z.[Han-Zi],
Real-Time High-Performance Semantic Image Segmentation of Urban
Street Scenes,
ITS(22), No. 6, June 2021, pp. 3258-3274.
IEEE DOI
2106
Semantics, Real-time systems, Image segmentation, Convolution,
Intelligent transportation systems, Task analysis,
light-weight convolutional neural networks
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Liu, M.Y.[Meng-Yu],
Yin, H.J.[Hu-Jun],
Efficient pyramid context encoding and feature embedding for semantic
segmentation,
IVC(111), 2021, pp. 104195.
Elsevier DOI
2106
Semantic segmentation, Convolutional neural networks,
Pyramid context encoding, Real-time processing
BibRef
Jin, Y.[Youngsaeng],
Han, D.[David],
Ko, H.S.[Han-Seok],
TrSeg: Transformer for semantic segmentation,
PRL(148), 2021, pp. 29-35.
Elsevier DOI
2107
Semantic segmentation, Scene understanding, Transformer,
Multi-scale contextual information
BibRef
Kreo, I.[Ivan],
Krapac, J.[Josip],
egvic, S.[Sinia],
Efficient Ladder-Style DenseNets for Semantic Segmentation of Large
Images,
ITS(22), No. 8, August 2021, pp. 4951-4961.
IEEE DOI
2108
BibRef
Earlier: A2, A1, A3:
Ladder-Style DenseNets for Semantic Segmentation of Large Natural
Images,
CVRoads17(238-245)
IEEE DOI
1802
BibRef
Earlier: A2, A3, Only:
Weakly-Supervised Semantic Segmentation by Redistributing Region Scores
Back to the Pixels,
GCPR16(377-388).
Springer DOI
1611
Semantics, Feature extraction, Image segmentation,
Computational modeling, Spatial resolution, Checkpointing,
road transportation.
Convolution, Tensile stress, Training
BibRef
Kreo, I.[Ivan],
Cauevic, D.[Denis],
Krapac, J.[Josip],
egvic, S.[Sinia],
Convolutional Scale Invariance for Semantic Segmentation,
GCPR16(64-75).
Springer DOI
1611
BibRef
Hu, J.[Jie],
Kong, H.F.[Hui-Fang],
Fan, L.[Lei],
Zhou, J.[Jun],
Enhancing feature fusion with spatial aggregation and channel fusion
for semantic segmentation,
IET-CV(15), No. 6, 2021, pp. 418-427.
DOI Link
2108
BibRef
Li, X.T.[Xiang-Tai],
Li, X.[Xia],
You, A.S.[An-Sheng],
Zhang, L.[Li],
Cheng, G.L.[Guang-Liang],
Yang, K.Y.[Kui-Yuan],
Tong, Y.H.[Yun-Hai],
Lin, Z.C.[Zhou-Chen],
Towards Efficient Scene Understanding via Squeeze Reasoning,
IP(30), 2021, pp. 7050-7063.
IEEE DOI
2108
Semantics, Cognition, Image segmentation, Task analysis,
Computational modeling, Convolution, Context modeling,
scene understanding
BibRef
Li, X.T.[Xiang-Tai],
Li, X.[Xia],
Zhang, L.[Li],
Cheng, G.L.[Guang-Liang],
Shi, J.P.[Jian-Ping],
Lin, Z.C.[Zhou-Chen],
Tan, S.H.[Shao-Hua],
Tong, Y.H.[Yun-Hai],
Improving Semantic Segmentation via Decoupled Body and Edge Supervision,
ECCV20(XVII:435-452).
Springer DOI
2011
BibRef
Hao, X.C.[Xiao-Chen],
Hao, X.J.[Xing-Jun],
Zhang, Y.[Yaru],
Li, Y.Y.[Yuan-Yuan],
Wu, C.[Chao],
Real-time semantic segmentation with weighted factorized-depthwise
convolution,
IVC(114), 2021, pp. 104269.
Elsevier DOI
2109
Semantic segmentation, Real-time, Pyramid fusion, Continuous separation
BibRef
Xiao, C.J.[Cun-Jun],
Hao, X.J.[Xing-Jun],
Li, H.B.[Hai-Bin],
Li, Y.Q.[Ya-Qian],
Zhang, W.M.[Wen-Ming],
Real-time semantic segmentation with local spatial pixel adjustment,
IVC(123), 2022, pp. 104470.
Elsevier DOI
2206
Semantic segmentation, Real-time, Local spatial adjustment, Dual-branch decoding
BibRef
Tang, Q.[Quan],
Liu, F.G.[Fa-Gui],
Zhang, T.[Tong],
Jiang, J.[Jun],
Zhang, Y.[Yu],
Attention-guided chained context aggregation for semantic
segmentation,
IVC(115), 2021, pp. 104309.
Elsevier DOI
2110
Semantic segmentation, Multi-scale contexts,
Series-parallel hybrid streams, Convolutional networks
BibRef
Cai, L.[Lile],
Xu, X.[Xun],
Zhang, L.N.[Li-Ning],
Foo, C.S.[Chuan-Sheng],
Exploring Spatial Diversity for Region-Based Active Learning,
IP(30), 2021, pp. 8702-8712.
IEEE DOI
2110
Uncertainty, Spatial diversity, Semantics, Image segmentation,
Task analysis, Labeling, Annotations, Active learning, semantic segmentation
BibRef
Zhang, J.[Jian],
Qi, L.[Lei],
Shi, Y.H.[Ying-Huan],
Gao, Y.[Yang],
Generalizable model-agnostic semantic segmentation via
target-specific normalization,
PR(122), 2022, pp. 108292.
Elsevier DOI
2112
Domain generalization, Semantic segmentation,
Model-agnostic learning, Target-specific normalization
BibRef
Yu, L.T.[Li-Tao],
Li, Z.B.[Zhi-Bin],
Xu, M.[Min],
Gao, Y.S.[Yong-Sheng],
Luo, J.B.[Jie-Bo],
Zhang, J.[Jian],
Distribution-Aware Margin Calibration for Semantic Segmentation in
Images,
IJCV(130), No. 1, January 2022, pp. 95-110.
Springer DOI
2201
BibRef
Zhou, Q.[Quan],
Wu, X.F.[Xiao-Fu],
Zhang, S.F.[Suo-Fei],
Kang, B.[Bin],
Ge, Z.Y.[Zong-Yuan],
Latecki, L.J.[Longin Jan],
Contextual ensemble network for semantic segmentation,
PR(122), 2022, pp. 108290.
Elsevier DOI
2112
Ensemble deconvolution, Semantic segmentation, FCNs,
Context aggregation, Encoder-decoder networks
BibRef
Liu, X.F.[Xiao-Feng],
Lu, Y.H.[Yun-Hong],
Liu, X.C.[Xiong-Chang],
Bai, S.[Song],
Li, S.[Site],
You, J.[Jane],
Wasserstein Loss With Alternative Reinforcement Learning for
Severity-Aware Semantic Segmentation,
ITS(23), No. 1, January 2022, pp. 587-596.
IEEE DOI
2201
Automobiles, Measurement, Roads, Semantics, Optimization, Training,
Histograms, Semantic segmentation, autonomous driving,
actor-critic
BibRef
Liu, X.F.[Xiao-Feng],
Ji, W.X.[Wen-Xuan],
You, J.[Jane],
El Fakhri, G.[Georges],
Woo, J.H.[Jong-Hye],
Severity-Aware Semantic Segmentation With Reinforced Wasserstein
Training,
CVPR20(12563-12572)
IEEE DOI
2008
Semantics, Autonomous vehicles, Measurement, Automobiles, Histograms,
Training, Roads
BibRef
Zhou, T.F.[Tian-Fei],
Li, L.L.[Liu-Lei],
Li, X.Y.[Xue-Yi],
Feng, C.M.[Chun-Mei],
Li, J.W.[Jian-Wu],
Shao, L.[Ling],
Group-Wise Learning for Weakly Supervised Semantic Segmentation,
IP(31), 2022, pp. 799-811.
IEEE DOI
2201
Semantics, Image segmentation, Training, Location awareness,
Cognition, Task analysis, Graph neural networks,
neural attention
BibRef
Chen, H.J.[Hong-Jun],
Wang, J.B.[Jin-Bao],
Chen, H.C.[Hong Cai],
Zhen, X.T.[Xian-Tong],
Zheng, F.[Feng],
Ji, R.R.[Rong-Rong],
Shao, L.[Ling],
Seminar Learning for Click-Level Weakly Supervised Semantic
Segmentation,
ICCV21(6900-6909)
IEEE DOI
2203
Seminars, Training, Knowledge engineering, Bridges, Costs, Annotations,
Segmentation, grouping and shape, Transfer/Low-shot/Semi/Unsupervised Learning
BibRef
Zhang, R.M.[Rui-Mao],
Lin, L.[Liang],
Wang, G.R.[Guang-Run],
Wang, M.[Meng],
Zuo, W.M.[Wang-Meng],
Hierarchical Scene Parsing by Weakly Supervised Learning with Image
Descriptions,
PAMI(41), No. 3, March 2019, pp. 596-610.
IEEE DOI
1902
Semantics, Labeling, Training, Neural networks, Task analysis,
Predictive models, Image segmentation, Scene parsing,
recursive structured prediction
BibRef
Lin, L.[Liang],
Wang, G.R.[Guang-Run],
Zhang, R.[Rui],
Zhang, R.M.[Rui-Mao],
Liang, X.D.[Xiao-Dan],
Zuo, W.M.[Wang-Meng],
Deep Structured Scene Parsing by Learning with Image Descriptions,
CVPR16(2276-2284)
IEEE DOI
1612
BibRef
Ma, T.Q.[Tian-Qi],
Wang, Q.L.[Qi-Long],
Zhang, H.Z.[Hong-Zhi],
Zuo, W.M.[Wang-Meng],
Delving Deeper Into Pixel Prior for Box-Supervised Semantic
Segmentation,
IP(31), 2022, pp. 1406-1417.
IEEE DOI
2202
Annotations, Semantics, Image segmentation, Training,
Benchmark testing, Predictive models, Convolution,
multiple instance learning
BibRef
Ge, C.[Ce],
Sun, H.F.[Hai-Feng],
Song, Y.Z.[Yi-Zhe],
Ma, Z.Y.[Zhan-Yu],
Liao, J.X.[Jian-Xin],
Exploring Local Detail Perception for Scene Sketch Semantic
Segmentation,
IP(31), 2022, pp. 1447-1461.
IEEE DOI
2202
Image segmentation, Semantics, Automobiles, Layout, Task analysis,
Feature extraction, Airplanes, Sketch dataset, scene sketch,
local detail perception
BibRef
Li, Q.[Qi],
Yang, W.X.[Wei-Xiang],
Liu, W.X.[Wen-Xi],
Yu, Y.L.[Yuan-Long],
He, S.F.[Sheng-Feng],
From Contexts to Locality: Ultra-high Resolution Image Segmentation
via Locality-aware Contextual Correlation,
ICCV21(7232-7241)
IEEE DOI
2203
Image segmentation, Image resolution, Correlation, Codes,
Computational modeling, Semantics, Segmentation,
Scene analysis and understanding
BibRef
Strudel, R.[Robin],
Garcia, R.[Ricardo],
Laptev, I.[Ivan],
Schmid, C.[Cordelia],
Segmenter: Transformer for Semantic Segmentation,
ICCV21(7242-7252)
IEEE DOI
2203
Image segmentation, Image coding, Semantics, Transformers, Encoding,
Decoding, Segmentation, grouping and shape,
Visual reasoning and logical representation
BibRef
Sakaridis, C.[Christos],
Dai, D.X.[Deng-Xin],
Van Gool, L.J.[Luc J.],
Map-Guided Curriculum Domain Adaptation and Uncertainty-Aware
Evaluation for Semantic Nighttime Image Segmentation,
PAMI(44), No. 6, June 2022, pp. 3139-3153.
IEEE DOI
2205
BibRef
Earlier:
Guided Curriculum Model Adaptation and Uncertainty-Aware Evaluation
for Semantic Nighttime Image Segmentation,
ICCV19(7373-7382)
IEEE DOI
2004
Semantics, Image segmentation, Adaptation models, Annotations,
Task analysis, Measurement, Lighting, Domain adaptation,
curriculum learning.
image annotation, learning (artificial intelligence), Uncertainty
BibRef
Zhang, B.F.[Bing-Feng],
Xiao, J.[Jimin],
Wei, Y.[Yunchao],
Huang, K.[Kaizhu],
Luo, S.[Shan],
Zhao, Y.[Yao],
End-to-end weakly supervised semantic segmentation with reliable
region mining,
PR(128), 2022, pp. 108663.
Elsevier DOI
2205
Weakly supervised, Semantic segmentation, End-to-end, Attention
BibRef
Jin, Z.C.[Zhen-Chao],
Liu, B.[Bin],
Chu, Q.[Qi],
Yu, N.H.[Neng-Hai],
ISNet: Integrate Image-Level and Semantic-Level Context for Semantic
Segmentation,
ICCV21(7169-7178)
IEEE DOI
2203
Image segmentation, Visualization, Lips, Aggregates, Semantics,
Benchmark testing, Segmentation, grouping and shape,
BibRef
Zhang, Y.[Yu],
Zhang, C.B.[Chang-Bin],
Jiang, P.T.[Peng-Tao],
Cheng, M.M.[Ming-Ming],
Mao, F.[Feng],
Personalized Image Semantic Segmentation,
ICCV21(10529-10539)
IEEE DOI
2203
Image segmentation, Correlation, Codes, Semantics,
Datasets and evaluation, Segmentation, grouping and shape
BibRef
Jain, S.[Shipra],
Paudel, D.P.[Danda Pani],
Danelljan, M.[Martin],
Van Gool, L.J.[Luc J.],
Scaling Semantic Segmentation Beyond 1K Classes on a Single GPU,
ICCV21(7406-7416)
IEEE DOI
2203
Training, Image segmentation, Computational modeling, Scalability,
Semantics, Graphics processing units, Object detection,
Representation learning
BibRef
Wang, W.G.[Wen-Guan],
Zhou, T.F.[Tian-Fei],
Yu, F.[Fisher],
Dai, J.F.[Ji-Feng],
Konukoglu, E.[Ender],
Van Gool, L.J.[Luc J.],
Exploring Cross-Image Pixel Contrast for Semantic Segmentation,
ICCV21(7283-7293)
IEEE DOI
2203
Training, Representation learning, Measurement, Image segmentation,
Semantics, Training data, Optical character recognition software,
Scene analysis and understanding
BibRef
Hsiao, C.W.[Chi-Wei],
Sun, C.[Cheng],
Chen, H.T.[Hwann-Tzong],
Sun, M.[Min],
Specialize and Fuse: Pyramidal Output Representation for Semantic
Segmentation,
ICCV21(7117-7126)
IEEE DOI
2203
Fuses, Aggregates, Semantics, Task analysis, Segmentation, grouping and shape
BibRef
Jin, Z.C.[Zhen-Chao],
Gong, T.[Tao],
Yu, D.D.[Dong-Dong],
Chu, Q.[Qi],
Wang, J.[Jian],
Wang, C.H.[Chang-Hu],
Shao, J.[Jie],
Mining Contextual Information Beyond Image for Semantic Segmentation,
ICCV21(7211-7221)
IEEE DOI
2203
Training, Image segmentation, Lips, Semantics, Memory modules,
Data aggregation, Segmentation, grouping and shape,
BibRef
Zhang, D.[Dong],
Zhang, H.[Hanwang],
Tang, J.H.[Jin-Hui],
Hua, X.S.[Xian-Sheng],
Sun, Q.[Qianru],
Self-Regulation for Semantic Segmentation,
ICCV21(6933-6943)
IEEE DOI
2203
Training, Visualization, Computational modeling, Semantics,
Neural networks, Performance gain, Segmentation,
Scene analysis and understanding
BibRef
Sun, W.X.[Wei-Xuan],
Zhang, J.[Jing],
Barnes, N.[Nick],
Inferring the Class Conditional Response Map for Weakly Supervised
Semantic Segmentation,
WACV22(2653-2662)
IEEE DOI
2202
Training, Image segmentation, Semantics, Pipelines,
Inference algorithms, Cams, Segmentation, Grouping and Shape
BibRef
Aakerberg, A.[Andreas],
Johansen, A.S.[Anders S.],
Nasrollahi, K.[Kamal],
Moeslund, T.B.[Thomas B.],
Semantic Segmentation Guided Real-World Super-Resolution,
RWSurvil22(449-458)
IEEE DOI
2202
Degradation, Training, Image segmentation, Adaptation models,
Visualization, Image color analysis, Superresolution
BibRef
Garcia, R.L.,
Happ, P.N.,
Feitosa, R.Q.,
Large Scale Semantic Segmentation of Virtual Environments to Facilitate
Corrosion Management,
ISPRS21(B2-2021: 465-470).
DOI Link
2201
BibRef
Pang, Y.T.[Yu-Ting],
Chang, J.[Jui],
Hsu, C.T.[Chiou-Ting],
Self-Guided Adversarial Learning for Domain Adaptive Semantic
Segmentation,
ICIP21(2249-2253)
IEEE DOI
2201
Learning systems, Image segmentation, Adaptation models, Semantics,
Benchmark testing, Reliability, Unsupervised domain adaptation,
self-guided adversarial learning
BibRef
Shiau, Z.Y.[Zu-Yun],
Lin, W.W.[Wei-Wei],
Lin, C.S.[Ci-Siang],
Wang, Y.C.A.F.[Yu-Chi-Ang Frank],
Meta-Learned Feature Critics for Domain Generalized Semantic
Segmentation,
ICIP21(2244-2248)
IEEE DOI
2201
Adaptation models, Visualization, Image segmentation, Semantics,
Benchmark testing, Feature extraction, domain generalization
BibRef
Lou, A.[Ange],
Loew, M.[Murray],
CFPNET: Channel-Wise Feature Pyramid for Real-Time Semantic
Segmentation,
ICIP21(1894-1898)
IEEE DOI
2201
Performance evaluation, Image segmentation, Convolution, Semantics,
Graphics processing units, Real-time semantic segmentation,
CFPNet
BibRef
Lee, H.J.[Hong Joo],
Ro, Y.M.[Yong Man],
Adversarially Robust Multi-Sensor Fusion Model Training Via Random
Feature Fusion for Semantic Segmentation,
ICIP21(339-343)
IEEE DOI
2201
Training, Image segmentation, Semantics, Data integration,
Object detection, Feature extraction, Multi-sensor data fusion,
random feature fusion
BibRef
Aakerberg, A.[Andreas],
Johansen, A.S.[Anders S.],
Nasrollahi, K.[Kamal],
Moeslund, T.B.[Thomas B.],
Single-Loss Multi-task Learning For Improving Semantic Segmentation
Using Super-Resolution,
CAIP21(II:403-411).
Springer DOI
2112
BibRef
Neven, R.[Robby],
Neven, D.[Davy],
de Brabandere, B.[Bert],
Proesmans, M.[Marc],
Goedemé, T.[Toon],
Weakly-Supervised Semantic Segmentation by Learning Label Uncertainty,
ILDAV21(1678-1686)
IEEE DOI
2112
Training, Deep learning, Image segmentation,
Uncertainty, Semantics, Neural networks
BibRef
Zhu, F.R.[Fang-Rui],
Zhu, Y.[Yi],
Zhang, L.[Li],
Wu, C.R.[Chong-Ruo],
Fu, Y.W.[Yan-Wei],
Li, M.[Mu],
A Unified Efficient Pyramid Transformer for Semantic Segmentation,
VSPW21(2667-2677)
IEEE DOI
2112
Adaptation models, Image segmentation,
Computational modeling, Semantics, Benchmark testing
BibRef
Dhingra, N.[Naina],
Chogovadze, G.[George],
Kunz, A.[Andreas],
Border-SegGCN: Improving Semantic Segmentation by Refining the Border
Outline using Graph Convolutional Network,
GSP-CV21(865-875)
IEEE DOI
2112
Computational modeling, Semantics,
Refining, Computer architecture, Prediction algorithms
BibRef
Shin, G.G.[Gyun-Gin],
Xie, W.[Weidi],
Albanie, S.[Samuel],
All you need are a few pixels: semantic segmentation with PixelPick,
ILDAV21(1687-1697)
IEEE DOI
2112
Training, Deep learning, Costs, Sensitivity, Annotations, Semantics,
Pipelines
BibRef
Holder, C.J.[Christopher J.],
Shafique, M.[Muhammad],
Efficient Uncertainty Estimation in Semantic Segmentation via
Distillation,
AVVision21(3080-3087)
IEEE DOI
2112
Training, Image segmentation, Uncertainty, Computational modeling,
Semantics, Predictive models, Data models
BibRef
Wu, T.[Tong],
Huang, J.[Junshi],
Gao, G.[Guangyu],
Wei, X.M.[Xiao-Ming],
Wei, X.L.[Xiao-Lin],
Luo, X.[Xuan],
Liu, C.H.[Chi Harold],
Embedded Discriminative Attention Mechanism for Weakly Supervised
Semantic Segmentation,
CVPR21(16760-16769)
IEEE DOI
2111
Image segmentation, Codes, Annotations, Semantics,
Collaboration, Feature extraction
BibRef
Cho, J.H.[Jang Hyun],
Mall, U.[Utkarsh],
Bala, K.[Kavita],
Hariharan, B.[Bharath],
PiCIE: Unsupervised Semantic Segmentation using Invariance and
Equivariance in Clustering,
CVPR21(16789-16799)
IEEE DOI
2111
Training, Visualization, Image segmentation, Codes,
Clustering methods, Semantics
BibRef
Huynh, C.[Chuong],
Tran, A.T.[Anh Tuan],
Luu, K.[Khoa],
Hoai, M.[Minh],
Progressive Semantic Segmentation,
CVPR21(16750-16759)
IEEE DOI
2111
Image segmentation, Image resolution, Codes,
Magnetic separation, Magnetic resonance imaging, Semantics
BibRef
Liu, M.[Mingyuan],
Schonfeld, D.[Dan],
Tang, W.[Wei],
Exploit Visual Dependency Relations for Semantic Segmentation,
CVPR21(9721-9730)
IEEE DOI
2111
Training, Deep learning, Visualization, Semantics,
Network architecture, Cognition
BibRef
Teja, S.P.[S. Prabhu],
Fleuret, F.[François],
Uncertainty Reduction for Model Adaptation in Semantic Segmentation,
CVPR21(9608-9618)
IEEE DOI
2111
Image segmentation, Adaptation models, Uncertainty, Semantics,
Urban areas, Feature extraction, Data models
BibRef
Lee, S.[Seungho],
Lee, M.[Minhyun],
Lee, J.[Jongwuk],
Shim, H.J.[Hyun-Jung],
Railroad is not a Train: Saliency as Pseudo-pixel Supervision for
Weakly Supervised Semantic Segmentation,
CVPR21(5491-5501)
IEEE DOI
2111
Location awareness, Training, Image segmentation,
Codes, Semantics, Pattern recognition
BibRef
Oh, Y.[Youngmin],
Kim, B.[Beomjun],
Ham, B.[Bumsub],
Background-Aware Pooling and Noise-Aware Loss for Weakly-Supervised
Semantic Segmentation,
CVPR21(6909-6918)
IEEE DOI
2111
Training, Image segmentation, Annotations,
Computational modeling, Semantics, Feature extraction
BibRef
Li, S.[Shuang],
Gong, K.X.[Kai-Xiong],
Liu, C.H.[Chi Harold],
Wang, Y.L.[Yu-Lin],
Qiao, F.[Feng],
Cheng, X.[Xinjing],
MetaSAug:
Meta Semantic Augmentation for Long-Tailed Visual Recognition,
CVPR21(5208-5217)
IEEE DOI
2111
Training, Visualization, Semantics,
Supervised learning, Training data, Benchmark testing
BibRef
Liu, Z.Z.[Zheng-Zhe],
Qi, X.J.[Xiao-Juan],
Fu, C.W.[Chi-Wing],
One Thing One Click: A Self-Training Approach for Weakly Supervised
3D Semantic Segmentation,
CVPR21(1726-1736)
IEEE DOI
2111
Training, Annotations, Semantics, Training data, Prototypes
BibRef
Yang, S.[Sibei],
Xia, M.[Meng],
Li, G.B.[Guan-Bin],
Zhou, H.Y.[Hong-Yu],
Yu, Y.Z.[Yi-Zhou],
Bottom-Up Shift and Reasoning for Referring Image Segmentation,
CVPR21(11261-11270)
IEEE DOI
2111
Location awareness, Visualization, Image segmentation,
Fuses, Message passing, Computational modeling
BibRef
Ma, H.Y.[Hao-Yu],
Lin, X.R.[Xiang-Ru],
Wu, Z.F.[Zi-Feng],
Yu, Y.Z.[Yi-Zhou],
Coarse-to-Fine Domain Adaptive Semantic Segmentation with Photometric
Alignment and Category-Center Regularization,
CVPR21(4050-4059)
IEEE DOI
2111
Image segmentation, Adaptation models,
Annotations, Computational modeling, Semantics, Pipelines
BibRef
Hänsch, R.[Ronny],
Looking Outside the Box: The Role of Context in Random Forest Based
Semantic Segmentation of PolSAR Images,
GCPR20(260-274).
Springer DOI
2110
BibRef
Zatsarynna, O.[Olga],
Sawatzky, J.[Johann],
Gall, J.[Juergen],
Discovering Latent Classes for Semi-supervised Semantic Segmentation,
GCPR20(202-217).
Springer DOI
2110
BibRef
Theodoridou, C.[Christina],
Kargakos, A.[Andreas],
Kostavelis, I.[Ioannis],
Giakoumis, D.[Dimitrios],
Tzovaras, D.[Dimitrios],
Spatially-Constrained Semantic Segmentation with Topological Maps and
Visual Embeddings,
CVS21(117-129).
Springer DOI
2109
BibRef
Szabó, A.[Attila],
Jamali-Rad, H.[Hadi],
Mannava, S.D.[Siva-Datta],
Tilted Cross-Entropy (TCE): Promoting Fairness in Semantic
Segmentation,
RCV21(2305-2310)
IEEE DOI
2109
Semantics, Performance analysis,
Pattern recognition, Risk management
BibRef
Adilova, L.[Linara],
Schulz, E.[Elena],
Akila, M.[Maram],
Houben, S.[Sebastian],
Schneider, J.D.[Jan David],
Hüger, F.[Fabian],
Wirtz, T.[Tim],
Plants Don't Walk on the Street: Common-Sense Reasoning for Reliable
Semantic Segmentation,
SAIAD21(85-92)
IEEE DOI
2109
Deep learning, Image segmentation, Semantics, Pipelines,
Probabilistic logic, Distortion
BibRef
Tavera, A.[Antonio],
Cermelli, F.[Fabio],
Masone, C.[Carlo],
Caputo, B.[Barbara],
Pixel-by-Pixel Cross-Domain Alignment for Few-Shot Semantic
Segmentation,
WACV22(1959-1968)
IEEE DOI
2202
Training, Image segmentation, Semantics,
Benchmark testing, Task analysis, Standards, Segmentation,
Grouping and Shape Scene Understanding
BibRef
Fontanel, D.[Dario],
Cermelli, F.[Fabio],
Mancini, M.[Massimiliano],
Caputo, B.[Barbara],
Detecting Anomalies in Semantic Segmentation with Prototypes,
SAIAD21(113-121)
IEEE DOI
2109
Training, Visualization, Computational modeling,
Semantics, Prototypes
BibRef
Arani, E.[Elahe],
Marzban, S.[Shabbir],
Pata, A.[Andrei],
Zonooz, B.[Bahram],
RGPNet: A Real-Time General Purpose Semantic Segmentation,
WACV21(3008-3017)
IEEE DOI
2106
Training, Performance evaluation, Adaptation models,
Computational modeling, Semantics, Green products
BibRef
Patel, Y.[Yash],
Appalaraju, S.[Srikar],
Manmatha, R.,
Saliency Driven Perceptual Image Compression,
WACV21(227-236)
IEEE DOI
2106
Measurement, Image segmentation, Image coding,
Computational modeling, Bit rate
BibRef
Yin, J.H.[Jun-Hui],
Zhang, S.Q.[Si-Qing],
Chang, D.L.[Dong-Liang],
Ma, Z.Y.[Zhan-Yu],
Guo, J.[Jun],
Dual-attention Guided Dropblock Module for Weakly Supervised Object
Localization,
ICPR21(4229-4236)
IEEE DOI
2105
weakly supervised object localization.
Location awareness, Training, Deep learning, Adaptation models,
Visualization, Automobiles
BibRef
Sun, Z.T.[Zi-Tang],
Kamata, S.I.[Sei-Ichiro],
Wang, R.J.[Ruo-Jing],
Semantic Segmentation Refinement Using Entropy and Boundary-guided
Monte Carlo Sampling and Directed Regional Search,
ICPR21(3931-3938)
IEEE DOI
2105
Monte Carlo methods, Semantics, Logic gates, Prediction algorithms,
Search problems, Entropy, Classification algorithms
BibRef
Rosas-Arias, L.[Leonel],
Benitez-Garcia, G.[Gibran],
Portillo-Portillo, J.[José],
Sánchez-Pérez, G.[Gabriel],
Yanai, K.[Keiji],
Fast and Accurate Real-Time Semantic Segmentation with Dilated
Asymmetric Convolutions,
ICPR21(2264-2271)
IEEE DOI
2105
Convolutional codes, Image resolution, Quantization (signal),
Semantics, Real-time systems, Decoding, Pattern recognition
BibRef
Zhang, B.[Bin],
Zhao, S.J.[Sheng-Jie],
Zhang, R.Q.[Rong-Qing],
Cross-Domain Semantic Segmentation of Urban Scenes via Multi-Level
Feature Alignment,
ICPR21(1912-1917)
IEEE DOI
2105
Image segmentation, Solid modeling, Semantics, Neural networks,
Virtual reality, Feature extraction, Robustness
BibRef
Zhang, Y.F.[Yi-Fei],
Sidibé, D.[Désiré],
Morel, O.[Olivier],
Meriaudeau, F.[Fabrice],
Multiscale Attention-Based Prototypical Network For Few-Shot Semantic
Segmentation,
ICPR21(7372-7378)
IEEE DOI
2105
Training, Image segmentation, Adaptation models, Annotations,
Semantics, Prototypes, Feature extraction
BibRef
Nie, D.[Dong],
Xue, J.[Jia],
Ren, X.F.[Xiao-Feng],
Bidirectional Pyramid Networks for Semantic Segmentation,
ACCV20(I:654-671).
Springer DOI
2103
BibRef
Ouni, A.[Achref],
Royer, E.[Eric],
Chevaldonné, M.[Marc],
Dhome, M.[Michel],
A Hybrid Approach for Improved Image Similarity Using Semantic
Segmentation,
ISVC20(II:647-657).
Springer DOI
2103
BibRef
Mozaffari, M.H.[M. Hamed],
Lee, W.S.[Won-Sook],
Semantic Segmentation with Peripheral Vision,
ISVC20(II:421-429).
Springer DOI
2103
BibRef
Huang, H.[Hang],
Zhi, P.[Peng],
Zhou, H.R.[Hao-Ran],
Zhang, Y.J.[Yu-Jin],
Wu, Q.[Qiang],
Yong, B.B.[Bin-Bin],
Tan, W.J.[Wei-Jun],
Zhou, Q.G.[Qing-Guo],
An Efficient Tiny Feature Map Network for Real-time Semantic
Segmentation,
ISVC20(II:332-343).
Springer DOI
2103
BibRef
Wu, Y.,
Jiang, A.,
Tang, Y.,
Kwan, H.K.,
GRNet: Deep Convolutional Neural Networks based on Graph Reasoning
for Semantic Segmentation,
VCIP20(116-119)
IEEE DOI
2102
Semantics, Convolution, Cognition, Image segmentation,
Feature extraction, Training, Network architecture,
semantic segmentation
BibRef
Huang, Y.,
Tang, Z.,
Su, K.,
Balance-batch: An Optimized Method for Semantic Segmentation Loss
Functions,
CVIDL20(342-346)
IEEE DOI
2102
feature extraction, image classification, image representation,
image segmentation, learning (artificial intelligence),
loss function
BibRef
Jiang, S.L.,
Li, G.,
Yao, W.,
Hong, Z.H.,
Kuc, T.Y.,
Dual Pyramids Encoder-decoder Network for Semantic Segmentation In
Ground and Aerial View Images,
ISPRS20(B2:605-610).
DOI Link
2012
BibRef
Zhang, T.Y.[Tian-Yi],
Lin, G.S.[Guo-Sheng],
Liu, W.D.[Wei-De],
Cai, J.F.[Jian-Fei],
Kot, A.[Alex],
Splitting Vs. Merging: Mining Object Regions with Discrepancy and
Intersection Loss for Weakly Supervised Semantic Segmentation,
ECCV20(XXII:663-679).
Springer DOI
2011
BibRef
Jing, Y.[Ya],
Kong, T.[Tao],
Wang, W.[Wei],
Wang, L.[Liang],
Li, L.[Lei],
Tan, T.N.[Tie-Niu],
Locate then Segment:
A Strong Pipeline for Referring Image Segmentation,
CVPR21(9853-9862)
IEEE DOI
2111
Location awareness, Image segmentation, Visualization, Fuses,
Pipelines, Object segmentation, Feature extraction
BibRef
Fan, J.S.[Jun-Song],
Zhang, Z.X.[Zhao-Xiang],
Tan, T.N.[Tie-Niu],
Employing Multi-estimations for Weakly-supervised Semantic Segmentation,
ECCV20(XVII:332-348).
Springer DOI
2011
BibRef
Chen, W.L.[Wan-Li],
Zhu, X.G.[Xin-Ge],
Sun, R.[Ruoqi],
He, J.[Junjun],
Li, R.[Ruiyu],
Shen, X.Y.[Xiao-Yong],
Yu, B.[Bei],
Tensor Low-rank Reconstruction for Semantic Segmentation,
ECCV20(XVII:52-69).
Springer DOI
2011
BibRef
Hu, H.Z.[Han-Zhe],
Ji, D.[Deyi],
Gan, W.H.[Wei-Hao],
Bai, S.[Shuai],
Wu, W.[Wei],
Yan, J.J.[Jun-Jie],
Class-wise Dynamic Graph Convolution for Semantic Segmentation,
ECCV20(XVII:1-17).
Springer DOI
2011
BibRef
Yin, M.H.[Ming-Hao],
Yao, Z.L.[Zhu-Liang],
Cao, Y.[Yue],
Li, X.[Xiu],
Zhang, Z.[Zheng],
Lin, S.[Stephen],
Hu, H.[Han],
Disentangled Non-local Neural Networks,
ECCV20(XV:191-207).
Springer DOI
2011
Code, Segmentation.
WWW Link.
WWW Link.
BibRef
Lehman, C.,
Temel, D.,
Alregib, G.,
On the Structures of Representation for the Robustness of Semantic
Segmentation to Input Corruption,
ICIP20(3239-3243)
IEEE DOI
2011
Robustness, Semantics, Entropy, Training, Estimation, Task analysis,
Machine learning, Robustness in Machine Learning,
Sigmoid
BibRef
Zhang, B.,
Zhao, S.,
Zhang, R.,
Towards Adaptive Semantic Segmentation By Progressive Feature
Refinement,
ICIP20(2221-2225)
IEEE DOI
2011
Image segmentation, Semantics, Task analysis, Adaptation models,
Machine learning, Computational modeling, Feature extraction,
deep learning
BibRef
Li, S.,
Zhou, Q.,
Liu, J.,
Wang, J.,
Fan, Y.,
Wu, X.,
Latecki, L.J.,
DCM: A Dense-Attention Context Module For Semantic Segmentation,
ICIP20(1431-1435)
IEEE DOI
2011
Convolution, Feature extraction, Semantics, Data mining,
Image segmentation, Kernel, Decoding, Semantic segmentation, Attention
BibRef
Chen, L.[Liyi],
Wu, W.W.[Wei-Wei],
Fu, C.C.[Chen-Chen],
Han, X.[Xiao],
Zhang, Y.T.[Yun-Tao],
Weakly Supervised Semantic Segmentation with Boundary Exploration,
ECCV20(XXVI:347-362).
Springer DOI
2011
BibRef
Liu, J.B.[Jian-Bo],
He, J.J.[Jun-Jun],
Zhang, J.W.[Jia-Wei],
Ren, J.S.[Jimmy S.],
Li, H.S.[Hong-Sheng],
Efficientfcn: Holistically-guided Decoding for Semantic Segmentation,
ECCV20(XXVI:1-17).
Springer DOI
2011
BibRef
Wang, Y.K.[Yu-Kang],
Zhou, W.[Wei],
Jiang, T.[Tao],
Bai, X.[Xiang],
Xu, Y.C.[Yong-Chao],
Intra-class Feature Variation Distillation for Semantic Segmentation,
ECCV20(VII:346-362).
Springer DOI
2011
BibRef
Michieli, U.[Umberto],
Borsato, E.[Edoardo],
Rossi, L.[Luca],
Zanuttigh, P.[Pietro],
Gmnet: Graph Matching Network for Large Scale Part Semantic
Segmentation in the Wild,
ECCV20(VIII:397-414).
Springer DOI
2011
BibRef
Yang, B.[Boyu],
Liu, C.[Chang],
Li, B.[Bohao],
Jiao, J.B.[Jian-Bin],
Ye, Q.X.[Qi-Xiang],
Prototype Mixture Models for Few-shot Semantic Segmentation,
ECCV20(VIII:763-778).
Springer DOI
2011
BibRef
Yuan, Y.H.[Yu-Hui],
Chen, X.L.[Xi-Lin],
Wang, J.D.[Jing-Dong],
Object-contextual Representations for Semantic Segmentation,
ECCV20(VI:173-190).
Springer DOI
2011
BibRef
Kamann, C.[Christoph],
Rother, C.[Carsten],
Increasing the Robustness of Semantic Segmentation Models with
Painting-by-numbers,
ECCV20(X:369-387).
Springer DOI
2011
BibRef
Liu, Y.F.[Yong-Fei],
Zhang, X.Y.[Xiang-Yi],
Zhang, S.Y.[Song-Yang],
He, X.M.[Xu-Ming],
Part-aware Prototype Network for Few-Shot Semantic Segmentation,
ECCV20(IX:142-158).
Springer DOI
2011
BibRef
He, Y.[Yang],
Rahimian, S.[Shadi],
Schiele, B.[Bernt],
Fritz, M.[Mario],
Segmentations-leak: Membership Inference Attacks and Defenses in
Semantic Image Segmentation,
ECCV20(XXIII:519-535).
Springer DOI
2011
BibRef
Xia, Y.D.[Ying-Da],
Zhang, Y.[Yi],
Liu, F.Z.[Feng-Ze],
Shen, W.[Wei],
Yuille, A.L.[Alan L.],
Synthesize Then Compare: Detecting Failures and Anomalies for Semantic
Segmentation,
ECCV20(I:145-161).
Springer DOI
2011
BibRef
Sun, G.L.[Guo-Lei],
Wang, W.G.[Wen-Guan],
Dai, J.F.[Ji-Feng],
Van Gool, L.J.[Luc J.],
Mining Cross-image Semantics for Weakly Supervised Semantic
Segmentation,
ECCV20(II:347-365).
Springer DOI
2011
BibRef
Luo, W.F.[Wen-Feng],
Yang, M.[Meng],
Semi-supervised Semantic Segmentation via Strong-weak Dual-branch
Network,
ECCV20(V:784-800).
Springer DOI
2011
BibRef
Cheng, H.K.[Ho Kei],
Chung, J.H.[Ji-Hoon],
Tai, Y.W.[Yu-Wing],
Tang, C.K.[Chi-Keung],
CascadePSP: Toward Class-Agnostic and Very High-Resolution
Segmentation via Global and Local Refinement,
CVPR20(8887-8896)
IEEE DOI
2008
Image segmentation, Image resolution, Semantics,
Computational modeling, Task analysis, Adaptation models, Feature extraction
BibRef
Oberdiek, P.,
Rottmann, M.,
Fink, G.A.,
Detection and Retrieval of Out-of-Distribution Objects in Semantic
Segmentation,
SAIAD20(1331-1340)
IEEE DOI
2008
Image segmentation, Feature extraction, Semantics, Visualization,
Agriculture, Machine learning, Image retrieval
BibRef
Zhen, M.,
Wang, J.,
Zhou, L.,
Li, S.,
Shen, T.,
Shang, J.,
Fang, T.,
Quan, L.,
Joint Semantic Segmentation and Boundary Detection Using Iterative
Pyramid Contexts,
CVPR20(13663-13672)
IEEE DOI
2008
Pattern recognition
BibRef
Kamann, C.,
Rother, C.,
Benchmarking the Robustness of Semantic Segmentation Models,
CVPR20(8825-8835)
IEEE DOI
2008
Robustness, Semantics, Computer architecture, Image segmentation,
Feature extraction, Benchmark testing, Cameras
BibRef
Chang, Y.,
Wang, Q.,
Hung, W.,
Piramuthu, R.,
Tsai, Y.,
Yang, M.,
Weakly-Supervised Semantic Segmentation via Sub-Category Exploration,
CVPR20(8988-8997)
IEEE DOI
2008
Task analysis, Feature extraction, Semantics, Training,
Image segmentation, Computational modeling
BibRef
Siddiqui, Y.,
Valentin, J.,
Nießner, M.,
ViewAL: Active Learning With Viewpoint Entropy for Semantic
Segmentation,
CVPR20(9430-9440)
IEEE DOI
2008
Entropy, Uncertainty, Semantics, Labeling, Image segmentation,
Task analysis, Data models
BibRef
Zhang, Y.,
Qiu, Z.,
Yao, T.,
Ngo, C.,
Liu, D.,
Mei, T.,
Transferring and Regularizing Prediction for Semantic Segmentation,
CVPR20(9618-9627)
IEEE DOI
2008
Semantics, Image segmentation, Roads, Buildings, Visualization,
Labeling, Adaptation models
BibRef
Wang, Y.[Yude],
Zhang, J.[Jie],
Kan, M.[Meina],
Shan, S.G.[Shi-Guang],
Chen, X.L.[Xi-Lin],
Self-Supervised Equivariant Attention Mechanism for Weakly Supervised
Semantic Segmentation,
CVPR20(12272-12281)
IEEE DOI
2008
Image segmentation, Semantics, Phase change materials,
Task analysis, Correlation, Aggregates, Supervised learning
BibRef
Araslanov, N.,
Roth, S.,
Single-Stage Semantic Segmentation From Image Labels,
CVPR20(4252-4261)
IEEE DOI
2008
Image segmentation, Training, Semantics, Task analysis, Logic gates,
Stochastic processes, Decoding
BibRef
Fan, J.,
Zhang, Z.,
Song, C.,
Tan, T.,
Learning Integral Objects With Intra-Class Discriminator for
Weakly-Supervised Semantic Segmentation,
CVPR20(4282-4291)
IEEE DOI
2008
Image segmentation, Semantics, Training, Task analysis, Manifolds,
Estimation, Benchmark testing
BibRef
Wang, L.,
Li, D.,
Zhu, Y.,
Tian, L.,
Shan, Y.,
Dual Super-Resolution Learning for Semantic Segmentation,
CVPR20(3773-3782)
IEEE DOI
2008
Semantics, Image segmentation, Spatial resolution, Task analysis,
Pose estimation, Convolution
BibRef
Li, Z.,
Bao, W.,
Zheng, J.,
Xu, C.,
Deep Grouping Model for Unified Perceptual Parsing,
CVPR20(4052-4062)
IEEE DOI
2008
Semantics, Task analysis, Computational modeling,
Image segmentation, Adaptation models, Context modeling, Message passing
BibRef
Lin, P.,
Sun, P.,
Cheng, G.,
Xie, S.,
Li, X.,
Shi, J.,
Graph-Guided Architecture Search for Real-Time Semantic Segmentation,
CVPR20(4202-4211)
IEEE DOI
2008
Computer architecture, Microprocessors, Semantics, Convolution,
Image segmentation, Real-time systems, Random variables
BibRef
Zareian, A.,
Karaman, S.,
Chang, S.,
Weakly Supervised Visual Semantic Parsing,
CVPR20(3733-3742)
IEEE DOI
2008
Semantics, Visualization, Proposals, Image edge detection,
Message passing, Task analysis
BibRef
Rai, S.N.,
Balasubramanian, V.N.,
Subramanian, A.,
Jawahar, C.V.,
Munich to Dubai: How far is it for Semantic Segmentation?,
WACV20(2988-2997)
IEEE DOI
2006
Image restoration, Image segmentation, Atmospheric modeling,
Meteorology, Semantics, Adaptation models, Training
BibRef
Du, Y.M.[Yu-Ming],
Xiao, Y.[Yang],
Lepetit, V.[Vincent],
Learning to Better Segment Objects from Unseen Classes with Unlabeled
Videos,
ICCV21(3355-3364)
IEEE DOI
2203
Training, Shape, Video sequences, Training data, Manuals,
Object segmentation, Object detection,
grouping and shape
BibRef
Stekovic, S.,
Fraundorfer, F.,
Lepetit, V.[Vincent],
Casting Geometric Constraints in Semantic Segmentation as
Semi-Supervised Learning,
WACV20(1843-1852)
IEEE DOI
2006
Image segmentation, Semantics, Predictive models,
Semisupervised learning, Task analysis, Training,
BibRef
Lin, H.[Hubert],
Upchurch, P.[Paul],
Bala, K.[Kavita],
Block Annotation:
Better Image Annotation With Sub-Image Decomposition,
ICCV19(5289-5299)
IEEE DOI
2004
Generate the data needed to do semantic segmentation.
image retrieval, image segmentation, image texture,
block annotation, high-quality pixel-level annotations, Quality control
BibRef
Yu, Z.,
Zhuge, Y.,
Lu, H.,
Zhang, L.,
Joint Learning of Saliency Detection and Weakly Supervised Semantic
Segmentation,
ICCV19(7222-7232)
IEEE DOI
2004
image classification, image coding, image recognition,
image segmentation, object detection, supervised learning, WSSS,
Computational modeling
BibRef
Kalluri, T.,
Varma, G.,
Chandraker, M.,
Jawahar, C.V.,
Universal Semi-Supervised Semantic Segmentation,
ICCV19(5258-5269)
IEEE DOI
2004
entropy, image segmentation, unsupervised learning,
cross-domain unsupervised losses, segmentation datasets, Roads
BibRef
Cheng, B.,
Chen, L.,
Wei, Y.,
Zhu, Y.,
Huang, Z.,
Xiong, J.,
Huang, T.,
Hwu, W.,
Shi, H.,
Uiuc, U.,
SPGNet: Semantic Prediction Guidance for Scene Parsing,
ICCV19(5217-5227)
IEEE DOI
2004
feature extraction, image coding, image segmentation,
learning (artificial intelligence), pose estimation, Feature extraction
BibRef
He, J.,
Deng, Z.,
Qiao, Y.,
Dynamic Multi-Scale Filters for Semantic Segmentation,
ICCV19(3561-3571)
IEEE DOI
2004
convolutional neural nets, image filtering, image representation,
image segmentation, Dynamic multiscale filters, Computational efficiency
BibRef
Pang, Y.,
Li, Y.,
Shen, J.,
Shao, L.,
Towards Bridging Semantic Gap to Improve Semantic Segmentation,
ICCV19(4229-4238)
IEEE DOI
2004
feature extraction, image enhancement, image fusion,
image representation, image segmentation, object detection, Convolution
BibRef
Zhang, C.,
Liwicki, S.,
Smith, W.,
Cipolla, R.,
Orientation-Aware Semantic Segmentation on Icosahedron Spheres,
ICCV19(3532-3540)
IEEE DOI
2004
convolutional neural nets, feature extraction,
image classification, image resolution, image segmentation, Task analysis
BibRef
Marin, D.[Dmitrii],
Boykov, Y.Y.[Yuri Y.],
Robust Trust Region for Weakly Supervised Segmentation,
ICCV21(6588-6598)
IEEE DOI
2203
Training, Deep learning, Image segmentation, Semantics,
Neural networks, Training data, Vision applications and systems
BibRef
Marin, D.,
He, Z.,
Vajda, P.,
Chatterjee, P.,
Tsai, S.,
Yang, F.,
Boykov, Y.Y.,
Efficient Segmentation: Learning Downsampling Near Semantic
Boundaries,
ICCV19(2131-2141)
IEEE DOI
2004
image sampling, image segmentation,
learning (artificial intelligence), semantic boundaries, Image resolution
BibRef
Nakajima, Y.,
Kang, B.,
Saito, H.,
Kitani, K.,
Incremental Class Discovery for Semantic Segmentation With RGBD
Sensing,
ICCV19(972-981)
IEEE DOI
2004
image colour analysis, image representation, image segmentation,
learning (artificial intelligence), object recognition,
Image color analysis
BibRef
Han, Q.Y.[Qiu-Yuan],
Zheng, J.[Jin],
Multi-scale Spatial Location Preference for Semantic Segmentation,
MMMod20(I:593-604).
Springer DOI
2003
BibRef
Shen, Y.H.[Yun-Hang],
Cao, L.J.[Liu-Juan],
Chen, Z.W.[Zhi-Wei],
Zhang, B.C.[Bao-Chang],
Su, C.[Chi],
Wu, Y.J.[Yong-Jian],
Huang, F.Y.[Fei-Yue],
Ji, R.R.[Rong-Rong],
Parallel Detection-and-Segmentation Learning for Weakly Supervised
Instance Segmentation,
ICCV21(8178-8188)
IEEE DOI
2203
Training, Image segmentation, Correlation, Pipelines, Coherence,
Object detection, Transfer/Low-shot/Semi/Unsupervised Learning,
grouping and shape
BibRef
Shen, Y.H.[Yun-Hang],
Ji, R.R.[Rong-Rong],
Wang, Y.[Yan],
Wu, Y.J.[Yong-Jian],
Cao, L.J.[Liu-Juan],
Cyclic Guidance for Weakly Supervised Joint Detection and Segmentation,
CVPR19(697-707).
IEEE DOI
2002
BibRef
Jiao, J.B.[Jian-Bo],
Wei, Y.[Yunchao],
Jie, Z.[Zequn],
Shi, H.H.[Hong-Hui],
Lau, R.W.H.[Rynson W.H.],
Huang, T.S.[Thomas S.],
Geometry-Aware Distillation for Indoor Semantic Segmentation,
CVPR19(2864-2873).
IEEE DOI
2002
BibRef
Liu, Y.[Yifan],
Chen, K.[Ke],
Liu, C.[Chris],
Qin, Z.C.[Zeng-Chang],
Luo, Z.[Zhenbo],
Wang, J.D.[Jing-Dong],
Structured Knowledge Distillation for Semantic Segmentation,
CVPR19(2599-2608).
IEEE DOI
2002
BibRef
Tian, Z.[Zhi],
He, T.[Tong],
Shen, C.H.[Chun-Hua],
Yan, Y.[Youliang],
Decoders Matter for Semantic Segmentation: Data-Dependent Decoding
Enables Flexible Feature Aggregation,
CVPR19(3121-3130).
IEEE DOI
2002
BibRef
Song, C.F.[Chun-Feng],
Huang, Y.[Yan],
Ouyang, W.L.[Wan-Li],
Wang, L.[Liang],
Box-Driven Class-Wise Region Masking and Filling Rate Guided Loss for
Weakly Supervised Semantic Segmentation,
CVPR19(3131-3140).
IEEE DOI
2002
BibRef
Zhou, Y.Z.[Yi-Zhou],
Sun, X.Y.[Xiao-Yan],
Zha, Z.J.[Zheng-Jun],
Zeng, W.J.[Wen-Jun],
Context-Reinforced Semantic Segmentation,
CVPR19(4041-4050).
IEEE DOI
2002
BibRef
Zhang, Z.Y.[Zhen-Yu],
Cui, Z.[Zhen],
Xu, C.Y.[Chun-Yan],
Yan, Y.[Yan],
Sebe, N.[Nicu],
Yang, J.[Jian],
Pattern-Affinitive Propagation Across Depth, Surface Normal and
Semantic Segmentation,
CVPR19(4101-4110).
IEEE DOI
2002
BibRef
Zhang, H.[Hang],
Zhang, H.[Han],
Wang, C.G.[Chen-Guang],
Xie, J.Y.[Jun-Yuan],
Co-Occurrent Features in Semantic Segmentation,
CVPR19(548-557).
IEEE DOI
2002
BibRef
He, T.[Tong],
Shen, C.H.[Chun-Hua],
Tian, Z.[Zhi],
Gong, D.[Dong],
Sun, C.M.[Chang-Ming],
Yan, Y.[Youliang],
Knowledge Adaptation for Efficient Semantic Segmentation,
CVPR19(578-587).
IEEE DOI
2002
BibRef
Chang, W.L.[Wei-Lun],
Wang, H.P.[Hui-Po],
Peng, W.H.[Wen-Hsiao],
Chiu, W.C.[Wei-Chen],
All About Structure: Adapting Structural Information Across Domains for
Boosting Semantic Segmentation,
CVPR19(1900-1909).
IEEE DOI
2002
BibRef
Schmitz, M.,
Brandenburger, W.,
Mayer, H.,
Semantic Segmentation of Airborne Images and Corresponding Digital
Surface Models - Additional Input Data Or Additional Task?,
PIA19(195-200).
DOI Link
1912
BibRef
Huang, Y.,
Proesmans, M.,
Georgoulis, S.,
Van Gool, L.J.,
Uncertainty based model selection for fast semantic segmentation,
MVA19(1-6)
DOI Link
1911
entropy, image segmentation, inference mechanisms, semantic labels,
baseline model, reasonable inference speeds,
Entropy
BibRef
Bevandic, P.[Petra],
Kreo, I.[Ivan],
Oric, M.[Marin],
egvic, S.[Sinia],
Simultaneous Semantic Segmentation and Outlier Detection in Presence of
Domain Shift,
GCPR19(33-47).
Springer DOI
1911
BibRef
Russo, P.[Paolo],
Tommasi, T.[Tatiana],
Caputo, B.[Barbara],
Towards Multi-source Adaptive Semantic Segmentation,
CIAP19(I:292-301).
Springer DOI
1909
BibRef
Leonardi, M.[Marco],
Mazzini, D.[Davide],
Schettini, R.[Raimondo],
Training Efficient Semantic Segmentation CNNs on Multiple Datasets,
CIAP19(II:303-314).
Springer DOI
1909
BibRef
Zhuang, P.C.[Peng-Cheng],
Sekikawa, Y.[Yusuke],
Hara, K.[Kosuke],
Saito, H.[Hideo],
Learning an Optimisable Semantic Segmentation Map with Image
Conditioned Variational Autoencoder,
CIAP19(II:379-389).
Springer DOI
1909
BibRef
Saha, S.[Sudipan],
Sudhakaran, S.[Swathikiran],
Banerjee, B.[Biplab],
Pendurkar, S.[Sumedh],
Semantic Guided Deep Unsupervised Image Segmentation,
CIAP19(II:499-510).
Springer DOI
1909
BibRef
Dias, P.A.[Philipe Ambrozio],
Medeiros, H.[Henry],
Semantic Segmentation Refinement by Monte Carlo Region Growing of High
Confidence Detections,
ACCV18(II:131-146).
Springer DOI
1906
BibRef
Falcăo, A.[Alexandre],
Bragantini, J.[Jordăo],
The Role of Optimum Connectivity in Image Segmentation:
Can the Algorithm Learn Object Information During the Process?,
DGCI19(180-194).
Springer DOI
1905
Feature space and image domain linkage.
BibRef
Guan, H.,
Zhang, Z.,
Tan, T.,
Inception Donut Convolution for Top-down Semantic Segmentation,
ICPR18(2492-2497)
IEEE DOI
1812
convolution, feature extraction, feedforward neural nets,
image representation, image segmentation, Streaming media
BibRef
Vallurupalli, N.,
Annamaneni, S.,
Varma, G.,
Jawahar, C.,
Mathew, M.,
Nagori, S.,
Efficient Semantic Segmentation Using Gradual Grouping,
ECVW18(711-7118)
IEEE DOI
1812
Training, Semantics, Computer architecture, Computational modeling,
Sparse matrices, Predictive models, Decoding
BibRef
Tsai, Y.,
Hung, W.,
Schulter, S.,
Sohn, K.,
Yang, M.,
Chandraker, M.,
Learning to Adapt Structured Output Space for Semantic Segmentation,
CVPR18(7472-7481)
IEEE DOI
1812
Image segmentation, Semantics, Adaptation models, Task analysis,
Training, Prediction algorithms, Layout
BibRef
Wei, Y.,
Xiao, H.,
Shi, H.,
Jie, Z.,
Feng, J.,
Huang, T.S.,
Revisiting Dilated Convolution: A Simple Approach for Weakly- and
Semi-Supervised Semantic Segmentation,
CVPR18(7268-7277)
IEEE DOI
1812
Image segmentation, Semantics, Convolution, Training, Kernel,
Standards, Head
BibRef
Muralikrishnan, S.,
Kim, V.G.,
Chaudhuri, S.,
Tags2Parts: Discovering Semantic Regions from Shape Tags,
CVPR18(2926-2935)
IEEE DOI
1812
Shape, Computer architecture, Image segmentation, Convolution,
Semantics, Training
BibRef
Bilinski, P.,
Prisacariu, V.[Victor],
Dense Decoder Shortcut Connections for Single-Pass Semantic
Segmentation,
CVPR18(6596-6605)
IEEE DOI
1812
Decoding, Semantics, Image segmentation, Architecture,
Computer architecture, Fuses, Spatial resolution
BibRef
Zhang, H.,
Dana, K.,
Shi, J.,
Zhang, Z.,
Wang, X.,
Tyagi, A.,
Agrawal, A.,
Context Encoding for Semantic Segmentation,
CVPR18(7151-7160)
IEEE DOI
1812
Encoding, Semantics, Convolution, Image segmentation, Training,
Image coding, Feature extraction
BibRef
Casanova, A.,
Cucurull, G.,
Drozdzal, M.,
Romero, A.,
Bengio, Y.,
On the Iterative Refinement of Densely Connected Representation
Levels for Semantic Segmentation,
AutoDrive18(1091-109109)
IEEE DOI
1812
Semantics, Spatial resolution, Computer architecture,
Convolutional codes, Computational modeling, Image segmentation
BibRef
Seifi, S.[Soroush],
Tuytelaars, T.[Tinne],
Attend and Segment: Attention Guided Active Semantic Segmentation,
ECCV20(XXV:305-321).
Springer DOI
2011
BibRef
Huang, Y.,
Jia, X.,
Georgoulis, S.,
Tuytelaars, T.,
Van Gool, L.J.,
Error Correction for Dense Semantic Image Labeling,
AutoDrive18(1111-11118)
IEEE DOI
1812
Image segmentation, Labeling, Task analysis, Semantics,
Error correction, Pipelines, Probability distribution
BibRef
Yang, M.,
Yu, K.,
Zhang, C.,
Li, Z.,
Yang, K.,
DenseASPP for Semantic Segmentation in Street Scenes,
CVPR18(3684-3692)
IEEE DOI
1812
Convolution, Semantics, Image resolution, Kernel, Image segmentation,
Neurons, Autonomous vehicles
BibRef
Matsuzuki, D.[Daisuke],
Hotta, K.[Kazuhiro],
Semantic Segmentation by Integrating Classifiers for Different
Difficulty Levels,
ISVC18(607-615).
Springer DOI
1811
BibRef
Ke, T.W.[Tsung-Wei],
Hwang, J.J.[Jyh-Jing],
Liu, Z.[Ziwei],
Yu, S.X.[Stella X.],
Adaptive Affinity Fields for Semantic Segmentation,
ECCV18(I: 605-621).
Springer DOI
1810
BibRef
Zhao, H.[Hengshuang],
Qi, X.J.[Xiao-Juan],
Shen, X.Y.[Xiao-Yong],
Shi, J.P.[Jian-Ping],
Jia, J.Y.[Jia-Ya],
ICNet for Real-Time Semantic Segmentation on High-Resolution Images,
ECCV18(III: 418-434).
Springer DOI
1810
BibRef
Lin, D.[Di],
Ji, Y.[Yuanfeng],
Lischinski, D.[Dani],
Cohen-Or, D.[Daniel],
Huang, H.[Hui],
Multi-scale Context Intertwining for Semantic Segmentation,
ECCV18(III: 622-638).
Springer DOI
1810
BibRef
Zhu, X.G.[Xin-Ge],
Zhou, H.[Hui],
Yang, C.Y.[Ce-Yuan],
Shi, J.P.[Jian-Ping],
Lin, D.[Dahua],
Penalizing Top Performers:
Conservative Loss for Semantic Segmentation Adaptation,
ECCV18(VII: 587-603).
Springer DOI
1810
BibRef
Zhang, Z.Y.[Zhen-Yu],
Cui, Z.[Zhen],
Xu, C.Y.[Chun-Yan],
Jie, Z.Q.[Ze-Qun],
Li, X.[Xiang],
Yang, J.[Jian],
Joint Task-Recursive Learning for Semantic Segmentation and Depth
Estimation,
ECCV18(X: 238-255).
Springer DOI
1810
BibRef
Mehta, S.[Sachin],
Rastegari, M.[Mohammad],
Caspi, A.[Anat],
Shapiro, L.[Linda],
Hajishirzi, H.[Hannaneh],
ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic
Segmentation,
ECCV18(X: 561-580).
Springer DOI
1810
BibRef
Zhang, Z.L.[Zhen-Li],
Zhang, X.Y.[Xiang-Yu],
Peng, C.[Chao],
Xue, X.Y.[Xiang-Yang],
Sun, J.[Jian],
ExFuse: Enhancing Feature Fusion for Semantic Segmentation,
ECCV18(X: 273-288).
Springer DOI
1810
BibRef
Sulimowicz, L.,
Ahmad, I.,
Aved, A.,
Superpixel-Enhanced Pairwise Conditional Random Field for Semantic
Segmentation,
ICIP18(271-275)
IEEE DOI
1809
Image segmentation, Semantics, Kernel, Labeling, Robustness,
Visualization, Image color analysis,
and Higher-order CRFs
BibRef
Lu, L.H.[Li-Hsien],
Hsu, C.T.[Chiou-Ting],
Semantic Segmentation for Real-World Data by Jointly Exploiting
Supervised andxs Transferrable Knowledge,
BMVC16(xx-yy).
HTML Version.
1805
BibRef
Chaurasia, A.,
Culurciello, E.,
LinkNet: Exploiting encoder representations for efficient semantic
segmentation,
VCIP17(1-4)
IEEE DOI
1804
image resolution, image segmentation,
learning (artificial intelligence), neural nets, LinkNet,
Training
BibRef
Zhang, Y.[Yu],
Ngan, K.N.[King Ngi],
Huynh, C.P.[Cong Phuoc],
Habili, N.[Nariman],
Learning Deep Spatial-Spectral Features for Material Segmentation in
Hyperspectral Images,
DICTA17(1-7)
IEEE DOI
1804
feature extraction, geophysical image processing,
image classification, image segmentation,
Training
BibRef
Cui, Z.,
Zhang, Q.,
Geng, S.,
Niu, X.,
Yang, J.,
Qiao, Y.,
Semantic segmentation with multi-path refinement and pyramid pooling
dilated-resnet,
ICIP17(3100-3104)
IEEE DOI
1803
Computer architecture, Convolution, Feature extraction,
Image segmentation, Semantics, Task analysis, Training,
Segmentation
BibRef
Zhu, Y.,
Tian, Y.,
Metaxas, D.,
Dollár, P.,
Semantic Amodal Segmentation,
CVPR17(3001-3009)
IEEE DOI
1711
Image edge detection, Image segmentation, Object detection,
Semantics, Tools, Visualization
BibRef
Vernaza, P.,
Chandraker, M.,
Learning Random-Walk Label Propagation for Weakly-Supervised Semantic
Segmentation,
CVPR17(2953-2961)
IEEE DOI
1711
Image edge detection, Image segmentation, Labeling, Semantics,
Training, Uncertainty
BibRef
Shen, F.,
Gan, R.,
Yan, S.,
Zeng, G.,
Semantic Segmentation via Structured Patch Prediction, Context CRF
and Guidance CRF,
CVPR17(5178-5186)
IEEE DOI
1711
Complexity theory, Image segmentation, Message passing,
Predictive models, Semantics, Training
BibRef
Luo, P.[Ping],
Wang, G.R.[Guang-Run],
Lin, L.[Liang],
Wang, X.G.[Xiao-Gang],
Deep Dual Learning for Semantic Image Segmentation,
ICCV17(2737-2745)
IEEE DOI
1802
BibRef
Earlier: A2, A1, A3, A4:
Learning Object Interactions and Descriptions for Semantic Image
Segmentation,
CVPR17(5235-5243)
IEEE DOI
1711
image reconstruction, image segmentation,
learning (artificial intelligence), neural nets, DIS,
Cleaning, Cows, Feature extraction, Image segmentation, Semantics,
Streaming media.
BibRef
Wigness, M.,
Rogers, J.G.,
Unsupervised Semantic Scene Labeling for Streaming Data,
CVPR17(5910-5919)
IEEE DOI
1711
Adaptation models, Data models, Image segmentation, Labeling,
Semantics, Streaming media, Visualization
BibRef
Bulň, S.R.,
Neuhold, G.,
Kontschieder, P.,
Loss Max-Pooling for Semantic Image Segmentation,
CVPR17(7082-7091)
IEEE DOI
1711
Benchmark testing, Image segmentation, Semantics, Standards,
Training, Upper, bound
BibRef
He, Y.[Yang],
Keuper, M.[Margret],
Schiele, B.[Bernt],
Fritz, M.[Mario],
Learning Dilation Factors for Semantic Segmentation of Street Scenes,
GCPR17(41-51).
Springer DOI
1711
BibRef
Jégou, S.[Simon],
Drozdzal, M.[Michal],
Vazquez, D.[David],
Romero, A.[Adriana],
Bengio, Y.[Yoshua],
The One Hundred Layers Tiramisu:
Fully Convolutional DenseNets for Semantic Segmentation,
CVVT17(1175-1183)
IEEE DOI
1709
Benchmark testing, Computer architecture, Image segmentation,
Semantics, Spatial resolution, Standards
BibRef
Derue, F.X.[François-Xavier],
Dahmane, M.[Mohamed],
Lalonde, M.[Marc],
Foucher, S.[Samuel],
Exploiting Semantic Segmentation for Robust Camera Motion
Classification,
ICIAR17(173-181).
Springer DOI
1706
BibRef
Huang, Q.[Qin],
Xia, C.Y.[Chun-Yang],
Zheng, W.[Wenchao],
Song, Y.H.[Yu-Hang],
Xu, H.[Hao],
Kuo, C.C.J.[C.C. Jay],
Object Boundary Guided Semantic Segmentation,
ACCV16(I: 197-212).
Springer DOI
1704
BibRef
Hazirbas, C.[Caner],
Ma, L.N.[Ling-Ni],
Domokos, C.[Csaba],
Cremers, D.[Daniel],
FuseNet: Incorporating Depth into Semantic Segmentation via
Fusion-Based CNN Architecture,
ACCV16(I: 213-228).
Springer DOI
1704
BibRef
Bouachir, W.,
Torabi, A.,
Bilodeau, G.A.,
Blais, P.,
A bag of words approach for semantic segmentation of monitored scenes,
ISIVC16(88-93)
IEEE DOI
1704
Bayes methods
BibRef
Souly, N.[Nasim],
Shah, M.[Mubarak],
Scene Labeling Using Sparse Precision Matrix,
CVPR16(3650-3658)
IEEE DOI
1612
BibRef
Xu, C.,
Corso, J.J.[Jason J.],
Actor-Action Semantic Segmentation with Grouping Process Models,
CVPR16(3083-3092)
IEEE DOI
1612
BibRef
Gao, Y.[Yang],
Beijbom, O.[Oscar],
Zhang, N.[Ning],
Darrell, T.J.[Trevor J.],
Compact Bilinear Pooling,
CVPR16(317-326)
IEEE DOI
1612
BibRef
Bearman, A.[Amy],
Russakovsky, O.[Olga],
Ferrari, V.[Vittorio],
Fei-Fei, L.[Li],
What's the Point: Semantic Segmentation with Point Supervision,
ECCV16(VII: 549-565).
Springer DOI
1611
BibRef
Ghiasi, G.[Golnaz],
Fowlkes, C.C.[Charless C.],
Laplacian Pyramid Reconstruction and Refinement for Semantic
Segmentation,
ECCV16(III: 519-534).
Springer DOI
1611
BibRef
Fourure, D.[Damien],
Emonet, R.[Rémi],
Fromont, E.[Elisa],
Muselet, D.[Damien],
Trémeau, A.[Alain],
Wolf, C.[Christian],
Semantic Segmentation via Multi-task, Multi-domain Learning,
SSSPR16(333-343).
Springer DOI
1611
BibRef
Xing, F.Z.,
Cambria, E.,
Huang, W.B.,
Xu, Y.,
Weakly supervised semantic segmentation with superpixel embedding,
ICIP16(1269-1273)
IEEE DOI
1610
Context
BibRef
Tarashima, S.,
Pan, J.,
Irie, G.,
Kurozumi, T.,
Kinebuchi, T.,
Joint object discovery and segmentation with image-wise
reconstruction error,
ICIP16(849-853)
IEEE DOI
1610
Airplanes
BibRef
Zhou, H.,
Zhang, J.[Jun],
Lei, J.[Jun],
Li, S.[Shuohao],
Tu, D.[Dan],
Image semantic segmentation based on FCN-CRF model,
ICIVC16(9-14)
IEEE DOI
1610
feature extraction
BibRef
Li, W.[Weihao],
Yang, M.Y.[Michael Ying],
Efficient Semantic Segmentation Of Man-made Scenes Using
Fully-connected Conditional Random Field,
ISPRS16(B3: 633-640).
DOI Link
1610
BibRef
Tian, Q.,
Li, B.,
Simultaneous semantic segmentation of a set of partially labeled
images,
WACV16(1-9)
IEEE DOI
1606
Computer science
BibRef
Najafi, M.[Mohammad],
Namin, S.T.[Sarah Taghavi],
Salzmann, M.[Mathieu],
Petersson, L.[Lars],
Sample and Filter: Nonparametric Scene Parsing via Efficient
Filtering,
CVPR16(607-615)
IEEE DOI
1612
BibRef
Earlier: A2, A1, A3, A4:
Cutting Edge: Soft Correspondences in Multimodal Scene Parsing,
ICCV15(1188-1196)
IEEE DOI
1602
Feature extraction. combine modalities.
BibRef
Qi, X.J.[Xiao-Juan],
Liu, Z.Z.[Zheng-Zhe],
Shi, J.P.[Jian-Ping],
Zhao, H.S.[Heng-Shuang],
Jia, J.Y.[Jia-Ya],
Augmented Feedback in Semantic Segmentation Under Image Level
Supervision,
ECCV16(VIII: 90-105).
Springer DOI
1611
BibRef
Qi, X.J.[Xiao-Juan],
Shi, J.P.[Jian-Ping],
Liu, S.,
Liao, R.,
Jia, J.Y.[Jia-Ya],
Semantic Segmentation with Object Clique Potential,
ICCV15(2587-2595)
IEEE DOI
1602
Computational modeling
BibRef
Varas, D.,
Alfaro, M.,
Marques, F.,
Multiresolution Hierarchy Co-Clustering for Semantic Segmentation in
Sequences with Small Variations,
ICCV15(4579-4587)
IEEE DOI
1602
Image resolution
BibRef
Deng, Z.,
Todorovic, S.,
Latecki, L.J.,
Semantic Segmentation of RGBD Images with Mutex Constraints,
ICCV15(1733-1741)
IEEE DOI
1602
Computational modeling
BibRef
Pourian, N.,
Karthikeyan, S.,
Manjunath, B.S.,
Weakly Supervised Graph Based Semantic Segmentation by Learning
Communities of Image-Parts,
ICCV15(1359-1367)
IEEE DOI
1602
Correlation
BibRef
Caesar, H.[Holger],
Uijlings, J.[Jasper],
Ferrari, V.[Vittorio],
Region-Based Semantic Segmentation with End-to-End Training,
ECCV16(I: 381-397).
Springer DOI
1611
BibRef
Earlier:
Joint Calibration for Semantic Segmentation,
BMVC15(xx-yy).
DOI Link
1601
BibRef
Srivatsa, R.S.[R. Sai],
Babu, R.V.[R. Venkatesh],
Salient object detection via objectness measure,
ICIP15(4481-4485)
IEEE DOI
1512
Image Saliency; Image Segmentation; Objectness Proposals; Superpixels
BibRef
Ventura, C.[Carles],
Giro-i-Nieto, X.[Xavier],
Vilaplana, V.[Veronica],
McGuinness, K.[Kevin],
Marques, F.[Ferran],
O'Connor, N.E.[Noel E.],
Improving spatial codification in semantic segmentation,
ICIP15(3605-3609)
IEEE DOI
1512
Object recognition
BibRef
Zhao, N.[Nan],
Banerjee, C.[Chaity],
Liu, X.W.[Xiu-Wen],
Nano-scale context-sensitive semantic segmentation,
ICIP15(3062-3066)
IEEE DOI
1512
Nano-scale; context-sensitive; microvilli; semantic segmentation; spike
BibRef
Pieck, M.A.R.[Martin A.R.],
van der Sommen, F.[Fons],
Zinger, S.[Svitlana],
de With, P.H.N.[Peter H.N.],
Real-time semantic context labeling for image understanding,
ICIP15(3180-3184)
IEEE DOI
1512
Context classification; Gabor filtering; SVM; Segmentation
BibRef
Dai, J.F.[Ji-Feng],
He, K.M.[Kai-Ming],
Sun, J.[Jian],
Convolutional feature masking for joint object and stuff segmentation,
CVPR15(3992-4000)
IEEE DOI
1510
BibRef
Mostajabi, M.[Mohammadreza],
Yadollahpour, P.[Payman],
Shakhnarovich, G.[Gregory],
Feedforward semantic segmentation with zoom-out features,
CVPR15(3376-3385)
IEEE DOI
1510
BibRef
Zhang, W.[Wei],
Zeng, S.[Sheng],
Wang, D.[Dequan],
Xue, X.Y.[Xiang-Yang],
Weakly supervised semantic segmentation for social images,
CVPR15(2718-2726)
IEEE DOI
1510
BibRef
Ardeshir, S.[Shervin],
Collins-Sibley, K.M.[Kofi Malcolm],
Shah, M.[Mubarak],
Geo-semantic segmentation,
CVPR15(2792-2799)
IEEE DOI
1510
BibRef
Sharma, A.[Abhishek],
Tuzel, O.[Oncel],
Jacobs, D.W.[David W.],
Deep hierarchical parsing for semantic segmentation,
CVPR15(530-538)
IEEE DOI
1510
BibRef
Zhu, G.[Gao],
Ming, Y.S.[Yan-Sheng],
Li, H.D.[Hong-Dong],
Object category detection by incorporating mid-level grouping cues,
ICIP14(1604-1608)
IEEE DOI
1502
Computer vision
BibRef
Bassiouny, A.[Ahmed],
El-Saban, M.[Motaz],
Semantic segmentation as image representation for scene recognition,
ICIP14(981-985)
IEEE DOI
1502
Accuracy
BibRef
Tegen, A.[Agnes],
Weegar, R.[Rebecka],
Hammarlund, L.[Linus],
Oskarsson, M.[Magnus],
Jiang, F.Y.[Fang-Yuan],
Medved, D.[Dennis],
Nugues, P.[Pierre],
Astrom, K.[Kalle],
Image Segmentation and Labeling Using Free-Form Semantic Annotation,
ICPR14(2281-2286)
IEEE DOI
1412
Context
BibRef
Kroeger, T.[Thorben],
Kappes, J.H.[Jörg H.],
Beier, T.[Thorsten],
Koethe, U.[Ullrich],
Hamprecht, F.A.[Fred A.],
Asymmetric Cuts: Joint Image Labeling and Partitioning,
GCPR14(199-211).
Springer DOI
1411
BibRef
Ladicky, L.[Lubor],
Shi, J.B.[Jian-Bo],
Pollefeys, M.[Marc],
Pulling Things out of Perspective,
CVPR14(89-96)
IEEE DOI
1409
Depth Estimation; Object Recognition; Semantic Segmentation
BibRef
Mottaghi, R.[Roozbeh],
Chen, X.J.[Xian-Jie],
Liu, X.B.[Xiao-Bai],
Cho, N.G.[Nam-Gyu],
Lee, S.W.[Seong-Whan],
Fidler, S.[Sanja],
Urtasun, R.[Raquel],
Yuille, A.L.[Alan L.],
The Role of Context for Object Detection and Semantic Segmentation in
the Wild,
CVPR14(891-898)
IEEE DOI
1409
BibRef
Isola, P.[Phillip],
Zoran, D.[Daniel],
Krishnan, D.[Dilip],
Adelson, E.H.[Edward H.],
Crisp Boundary Detection Using Pointwise Mutual Information,
ECCV14(III: 799-814).
Springer DOI
1408
Between semantic objects.
BibRef
Li, Z.Y.[Zhen-Yang],
Gavves, E.[Efstratios],
Mensink, T.[Thomas],
Snoek, C.G.M.[Cees G.M.],
Attributes Make Sense on Segmented Objects,
ECCV14(VI: 350-365).
Springer DOI
1408
BibRef
Dong, J.[Jian],
Chen, Q.A.[Qi-Ang],
Yan, S.C.[Shui-Cheng],
Yuille, A.L.[Alan L.],
Towards Unified Object Detection and Semantic Segmentation,
ECCV14(V: 299-314).
Springer DOI
1408
Joint detect and segment.
BibRef
Riemenschneider, H.[Hayko],
Bódis-Szomorú, A.[András],
Weissenberg, J.[Julien],
Van Gool, L.J.[Luc J.],
Learning Where to Classify in Multi-view Semantic Segmentation,
ECCV14(V: 516-532).
Springer DOI
1408
BibRef
Tao, L.L.[Ling-Ling],
Porikli, F.M.[Fatih M.],
Vidal, R.[René],
Sparse Dictionaries for Semantic Segmentation,
ECCV14(V: 549-564).
Springer DOI
1408
BibRef
Zhu, S.Q.[Sheng-Qi],
Yang, Y.Q.[Yi-Qing],
Zhang, L.[Li],
From Label Maps to Label Strokes:
Semantic Segmentation for Street Scenes from Incomplete Training Data,
CVCP13(468-475)
IEEE DOI
1403
data handling
BibRef
Baek, S.[Seung_Ryul],
Lim, T.[Taegyu],
Heo, Y.S.[Yong Seok],
Park, S.B.[Sung-Bum],
Kwak, H.[Hantak],
Shim, W.[Woosung],
Superpixel Coherency and Uncertainty Models for Semantic Segmentation,
PGMs13(275-282)
IEEE DOI
1403
computational complexity
BibRef
Roig, G.[Gemma],
Boix, X.[Xavier],
de Nijs, R.[Roderick],
Ramos, S.[Sebastian],
Kuhnlenz, K.[Koljia],
Van Gool, L.J.[Luc J.],
Active MAP Inference in CRFs for Efficient Semantic Segmentation,
ICCV13(2312-2319)
IEEE DOI
1403
using expensive features.
BibRef
Barron, J.T.[Jonathan T.],
Biggin, M.D.[Mark D.],
Arbelaez, P.[Pablo],
Knowles, D.W.[David W.],
Keranen, S.V.E.[Soile V.E.],
Malik, J.[Jitendra],
Volumetric Semantic Segmentation Using Pyramid Context Features,
ICCV13(3448-3455)
IEEE DOI
1403
BibRef
Singh, G.[Gautam],
Kosecka, J.[Jana],
Introspective semantic segmentation,
WACV14(714-720)
IEEE DOI
1406
BibRef
Earlier:
Nonparametric Scene Parsing with Adaptive Feature Relevance and
Semantic Context,
CVPR13(3151-3157)
IEEE DOI
1309
feature relevance; scene understanding; semantic segmentation.
Small patches, simple features.
Accuracy.
BibRef
Csurka, G.[Gabriela],
Larlus, D.[Diane],
Perronnin, F.[Florent],
What is a good evaluation measure for semantic segmentation?,
BMVC13(xx-yy).
DOI Link
1402
BibRef
Li, F.X.[Fu-Xin],
Carreira, J.[Joao],
Lebanon, G.[Guy],
Sminchisescu, C.[Cristian],
Composite Statistical Inference for Semantic Segmentation,
CVPR13(3302-3309)
IEEE DOI
1309
composite likelihood
BibRef
Ying, P.[Peng],
Liu, J.[Jing],
Lu, H.Q.[Han-Qing],
Dictionary learning based superpixels clustering for
weakly-supervised semantic segmentation,
ICIP15(4258-4262)
IEEE DOI
1512
Weak supervision;dictionary learning;semantic segmentation
BibRef
Liu, Y.[Yang],
Liu, J.[Jing],
Li, Z.[Zechao],
Tang, J.H.[Jin-Hui],
Lu, H.Q.[Han-Qing],
Weakly-Supervised Dual Clustering for Image Semantic Segmentation,
CVPR13(2075-2082)
IEEE DOI
1309
Image Semantic Segmentation; Weakly-Supervised
BibRef
Zou, W.B.[Wen-Bin],
Kpalma, K.[Kidiyo],
Ronsin, J.[Joseph],
Semantic image segmentation using region bank,
ICPR12(922-925).
WWW Link.
1302
BibRef
And:
Semantic segmentation via sparse coding over hierarchical regions,
ICIP12(2577-2580).
IEEE DOI
1302
Hierarchical region segmentation, sparse coding of regions for recognition.
BibRef
Fröhlich, B.[Björn],
Rodner, E.[Erik],
Denzler, J.[Joachim],
Semantic Segmentation with Millions of Features:
Integrating Multiple Cues in a Combined Random Forest Approach,
ACCV12(I:218-231).
Springer DOI
1304
BibRef
And:
As Time Goes by:
Anytime Semantic Segmentation with Iterative Context Forests,
DAGM12(1-10).
Springer DOI
1209
BibRef
Hariharan, B.[Bharath],
Zitnick, C.L.[C. Lawrence],
Dollar, P.[Piotr],
Detecting Objects Using Deformation Dictionaries,
CVPR14(1995-2002)
IEEE DOI
1409
BibRef
Fidler, S.[Sanja],
Mottaghi, R.[Roozbeh],
Yuille, A.L.[Alan L.],
Urtasun, R.[Raquel],
Bottom-Up Segmentation for Top-Down Detection,
CVPR13(3294-3301)
IEEE DOI
1309
Object detection; object class recognition; object segmentation
BibRef
Yao, J.[Jian],
Fidler, S.[Sanja],
Urtasun, R.[Raquel],
Describing the scene as a whole: Joint object detection, scene
classification and semantic segmentation,
CVPR12(702-709).
IEEE DOI
1208
BibRef
Pohlen, T.,
Badami, I.,
Mathias, M.,
Leibe, B.[Bastian],
Semantic segmentation of modular furniture,
WACV16(1-9)
IEEE DOI
1606
Face
BibRef
Floros, G.[Georgios],
Rematas, K.[Konstantinos],
Leibe, B.[Bastian],
Multi-Class Image Labeling with Top-Down Segmentation and Generalized
Robust P^N Potentials,
BMVC11(xx-yy).
HTML Version.
1110
BibRef
Passino, G.[Giuseppe],
Patras, I.[Ioannis],
Izquierdo, E.[Ebroul],
Pyramidal Model for Image Semantic Segmentation,
ICPR10(1554-1557).
IEEE DOI
1008
BibRef
Schnitman, Y.[Yaar],
Caspi, Y.[Yaron],
Cohen-Or, D.[Daniel],
Lischinski, D.[Dani],
Inducing Semantic Segmentation from an Example,
ACCV06(II:373-384).
Springer DOI
0601
BibRef
Zhang, H.H.[Hong-Hui],
Xiao, J.X.[Jian-Xiong],
Quan, L.[Long],
Supervised Label Transfer for Semantic Segmentation of Street Scenes,
ECCV10(V: 561-574).
Springer DOI
1009
Set of labelled images of street scenes. Recognition is by matching
at image level, then using the given lables.
BibRef
Chapter on 2-D Region Segmentation Techniques, Snakes, Active Contours continues in
Domain Adaption for Semantic Segmentation .