8.6.3 Semantic Segmentation, Label and Segment Together

Zheng, C.[Chen], Zhang, Y.[Yun], Wang, L.G.[Lei-Guang],
Semantic Segmentation of Remote Sensing Imagery Using an Object-Based Markov Random Field Model With Auxiliary Label Fields,
GeoRS(55), No. 5, May 2017, pp. 3015-3028.
IEEE DOI 1705
Markov processes, image segmentation, remote sensing, auxiliary label field, hierarchical semantic information, object-based MRF model, object-based Markov random field model, probability distribution, remote sensing imagery, remote sensing images, semantic segmentation, Context, Context modeling, Image segmentation, Probability distribution, Remote sensing, Semantics, Spatial resolution, Auxiliary label field, object-based Markov random field, remote sensing image, semantic, segmentation BibRef

Zheng, C.[Chen], Pan, X.X.[Xin-Xin], Chen, X.H.[Xiao-Hui], Yang, X.H.[Xiao-Hui], Xin, X.[Xin], Su, L.M.[Li-Min],
An Object-Based Markov Random Field Model with Anisotropic Penalty for Semantic Segmentation of High Spatial Resolution Remote Sensing Imagery,
RS(11), No. 23, 2019, pp. xx-yy.
DOI Link 1912
BibRef

Czúni, L.[László], Rashad, M.[Metwally],
The use of IMUs for video object retrieval in lightweight devices,
JVCIR(48), No. 1, 2017, pp. 30-42.
Elsevier DOI 1708
BibRef
Earlier:
View centered video-based object recognition for lightweight devices,
WSSIP16(1-4)
IEEE DOI 1608
Video object retrieval. image recognition BibRef

Czuni, L.[Laszlo], Kiss, P.J.[Peter Jozsef], Lipovits, A.[Agnes], Gal, M.[Monika],
Lightweight mobile object recognition,
ICIP14(3426-3428)
IEEE DOI 1502
Cameras CEDD (Color and Edge Directivity Descriptor). BibRef

Marmanis, D., Schindler, K., Wegner, J.D., Galliani, S., Datcu, M., Stilla, U.,
Classification with an edge: Improving semantic image segmentation with boundary detection,
PandRS(135), No. Supplement C, 2018, pp. 158-172.
Elsevier DOI 1712
BibRef

Zhang, Y.[Yu], Chen, X.W.[Xiao-Wu], Li, J.[Jia], Wang, C.[Chen], Xia, C.Q.[Chang-Qun], Li, J.[Jun],
Semantic Object Segmentation in Tagged Videos via Detection,
PAMI(40), No. 7, July 2018, pp. 1741-1754.
IEEE DOI 1806
Image segmentation, Motion segmentation, Object segmentation, Proposals, Semantics, Spatiotemporal phenomena, Videos, weakly supervised segmentation BibRef

Zhang, Y.[Yu], Chen, X.W.[Xiao-Wu], Li, J.[Jia], Teng, W.[Wei], Song, H.[Haokun],
Exploring Weakly Labeled Images for Video Object Segmentation With Submodular Proposal Selection,
IP(27), No. 9, September 2018, pp. 4245-4259.
IEEE DOI 1807
computer vision, data mining, image matching, image segmentation, learning (artificial intelligence), video signal processing, weakly labeled video BibRef

Zhang, Y.[Yu], Chen, X.W.[Xiao-Wu], Li, J.[Jia], Wang, C.[Chen], Xia, C.Q.[Chang-Qun],
Semantic object segmentation via detection in weakly labeled video,
CVPR15(3641-3649)
IEEE DOI 1510
BibRef

Zhang, J.[Jing], Mu, Y.[Yakun], Feng, S.W.[Sheng-Wei], Li, K.H.[Ke-Huang], Yuan, Y.[Yubo], Lee, C.H.[Chin-Hui],
Image region annotation based on segmentation and semantic correlation analysis,
IET-IPR(12), No. 8, August 2018, pp. 1331-1337.
DOI Link 1808
BibRef

Shi, H., Li, H., Meng, F., Wu, Q., Xu, L., Ngan, K.N.,
Hierarchical Parsing Net: Semantic Scene Parsing From Global Scene to Objects,
MultMed(20), No. 10, October 2018, pp. 2670-2682.
IEEE DOI 1810
backpropagation, feature extraction, image classification, image coding, local appearance features, contextual feature, context learning BibRef

Noormohamadi, N.[Neda], Adibi, P.[Peyman], Ehsani, S.M.S.[Sayyed Mohammad Saeed],
Semantic image segmentation using an improved hierarchical graphical model,
IET-IPR(12), No. 11, November 2018, pp. 1943-1950.
DOI Link 1810
BibRef

Ates, H.F.[Hasan F.], Sunetci, S.[Sercan],
Multi-hypothesis contextual modeling for semantic segmentation,
PRL(117), 2019, pp. 104-110.
Elsevier DOI 1901
Image parsing, Segmentation, Superpixel, MRF BibRef

Zhou, H.[Hao], Han, A.[Anqi], Yang, H.D.[Hao-Dong], Zhang, J.[Jun],
Edge gradient feature and long distance dependency for image semantic segmentation,
IET-CV(13), No. 1, February 2019, pp. 53-60.
DOI Link 1902
BibRef

Joy, T.[Thomas], Desmaison, A.[Alban], Ajanthan, T.[Thalaiyasingam], Bunel, R.[Rudy], Salzmann, M.[Mathieu], Kohli, P.[Pushmeet], Torr, P.H.S.[Philip H. S.], Kumar, M.P.[M. Pawan],
Efficient Relaxations for Dense CRFs with Sparse Higher-Order Potentials,
SIIMS(12), No. 1, 2019, pp. 287-318.
DOI Link 1904
Segmentation and stereo matching. BibRef

Blott, G.[Gregor], Takami, M.[Masato], Heipke, C.[Christian],
Semantic Segmentation of Fisheye Images,
CVRoads18(I:181-196).
Springer DOI 1905
BibRef

Li, X., Ma, H., Luo, X.,
Weaklier Supervised Semantic Segmentation With Only One Image Level Annotation per Category,
IP(29), No. 1, 2020, pp. 128-141.
IEEE DOI 1910
image recognition, image segmentation, object recognition, supervised learning, weaklier supervised semantic segmentation, dual-branch iterative learning BibRef

Song, Y., Ou, Z.,
Semi-Supervised Seq2seq Joint-Stochastic-Approximation Autoencoders With Applications to Semantic Parsing,
SPLetters(27), 2020, pp. 31-35.
IEEE DOI 2001
Semi-supervised learning, seq2seq, semantic parsing, joint stochastic approximation, variational auto-encoder BibRef

Shimoda, W.[Wataru], Yanai, K.[Keiji],
Weakly supervised semantic segmentation using distinct class specific saliency maps,
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 Segmentation,
ICCV19(5207-5216)
IEEE DOI 2004
estimation theory, image denoising, image segmentation, iterative methods, learning (artificial intelligence), Predictive models BibRef

Zhang, J.[Jing], Lin, S.[Shaofu], Ding, L.[Lei], Bruzzone, L.[Lorenzo],
Multi-Scale Context Aggregation for Semantic Segmentation of Remote Sensing Images,
RS(12), No. 4, 2020, pp. xx-yy.
DOI Link 2003
BibRef

Toldo, M.[Marco], Michieli, U.[Umberto], Agresti, G.[Gianluca], Zanuttigh, P.[Pietro],
Unsupervised domain adaptation for mobile semantic segmentation based on cycle consistency and feature alignment,
IVC(95), 2020, pp. 103889.
Elsevier DOI 2004
Unsupervised domain adaptation, Semantic segmentation, Adversarial learning, Transfer learning, Image-to-image translation BibRef

Yang, Z.E.[Zheng-Eng], Yu, H.S.[Hong-Shan], Feng, M.T.[Ming-Tao], Sun, W.[Wei], Lin, X.F.[Xue-Fei], Sun, M.G.[Min-Gui], Mao, Z.H.[Zhi-Hong], Mian, A.[Ajmal],
Small Object Augmentation of Urban Scenes for Real-Time Semantic Segmentation,
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, synthetic dataset BibRef

Valada, A.[Abhinav], Mohan, R.[Rohit], Burgard, W.[Wolfram],
Self-Supervised Model Adaptation for Multimodal Semantic Segmentation,
IJCV(128), No. 5, May 2020, pp. 1239-1285.
Springer DOI 2005
BibRef

Wang, X.[Xiang], Liu, S.F.[Si-Fei], Ma, H.M.[Hui-Min], Yang, M.H.[Ming-Hsuan],
Weakly-Supervised Semantic Segmentation by Iterative Affinity Learning,
IJCV(128), No. 6, June 2020, pp. 1736-1749.
Springer DOI 2006
BibRef

Li, R.[Rui], Cao, W.M.[Wen-Ming], Jiao, Q.[Qianfen], Wu, S.[Si], Wong, H.S.[Hau-San],
Simplified unsupervised image translation for semantic segmentation adaptation,
PR(105), 2020, pp. 107343.
Elsevier DOI 2006
Domain adaptation, Image segmentation, Image translation BibRef

El Houfi, S.[Safae], Majda, A.[Aicha],
Efficient use of recent progresses for Real-time Semantic segmentation,
MVA(31), No. 6, August 2020, pp. Article45.
WWW Link. 2008
BibRef

Chen, Y.[Yifu], Dapogny, A.[Arnaud], Cord, M.[Matthieu],
SEMEDA: Enhancing segmentation precision with semantic edge aware loss,
PR(108), 2020, pp. 107557.
Elsevier DOI 2008
Semantic segmentation, Loss function, Computer vision BibRef

Vu, T., Jain, H., Bucher, M., Cord, M., Pérez, P.P.,
DADA: Depth-Aware Domain Adaptation in Semantic Segmentation,
ICCV19(7363-7372)
IEEE DOI 2004
data models, image segmentation, DADA, depth-aware domain adaptation, unsupervised domain adaptation, Benchmark testing BibRef

Seed picking crossover optimisation algorithm for semantic segmentation from images,
IET-IPR(14), No. 11, September 2020, pp. 2503-2511.
DOI Link 2009
No Authors Listed 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
Computer vision, Pattern recognition BibRef

Hoang, T.M., Zhou, J., Fan, Y.,
Image Compression with Encoder-Decoder Matched Semantic Segmentation,
CLIC20(619-623)
IEEE DOI 2008
Semantics, Image segmentation, Image coding, Conferences, Image reconstruction, Decoding, Codecs 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, Computer vision 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., Zhang, J., Kan, M., Shan, S., Chen, X.,
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

Liu, X., Ji, W., You, J., El Fakhri, G., Woo, J.,
Severity-Aware Semantic Segmentation With Reinforced Wasserstein Training,
CVPR20(12563-12572)
IEEE DOI 2008
Semantics, Autonomous vehicles, Measurement, Automobiles, Histograms, Training, Roads BibRef

Jaritz, M., Vu, T., de Charette, R., Wirbel, E., Pérez, P.,
xMUDA: Cross-Modal Unsupervised Domain Adaptation for 3D Semantic Segmentation,
CVPR20(12602-12611)
IEEE DOI 2008
Semantics, Image segmentation, Task analysis, Laser radar, Training 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

Pan, F., Shin, I., Rameau, F., Lee, S., Kweon, I.S.,
Unsupervised Intra-Domain Adaptation for Semantic Segmentation Through Self-Supervision,
CVPR20(3763-3772)
IEEE DOI 2008
Adaptation models, Entropy, Image segmentation, Semantics, Generators, Data models, Task analysis 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

Yang, Y., Soatto, S.,
FDA: Fourier Domain Adaptation for Semantic Segmentation,
CVPR20(4084-4094)
IEEE DOI 2008
Semantics, Image segmentation, Training, Entropy, Adaptation models, Task analysis, Frequency-domain analysis 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, Computer vision BibRef

Wang, Z., Wei, Y., Feris, R., Xiong, J., Hwu, W., Huang, T.S., Shi, H.,
Alleviating Semantic-level Shift: A Semi-supervised Domain Adaptation Method for Semantic Segmentation,
VL3W20(4043-4047)
IEEE DOI 2008
Semantics, Task analysis, Adaptation models, Image segmentation, Training, Feature extraction, Urban areas 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

Stekovic, S., Fraundorfer, F., Lepetit, V.,
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

Sakaridis, C.[Christos], Dai, D.[Dengxin], Van Gool, L.J.[Luc J.],
Guided Curriculum Model Adaptation and Uncertainty-Aware Evaluation for Semantic Nighttime Image Segmentation,
ICCV19(7373-7382)
IEEE DOI 2004
image annotation, image segmentation, learning (artificial intelligence), Uncertainty 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., He, Z., Vajda, P., Chatterjee, P., Tsai, S., Yang, F., Boykov, 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

Shukla, S., Van Gool, L.J., Timofte, R.,
Extremely Weak Supervised Image-to-Image Translation for Semantic Segmentation,
AIM19(3368-3377)
IEEE DOI 2004
image classification, image segmentation, supervised learning, unsupervised learning, generative models, adversarial training, semi supervised learning BibRef

Luo, Y., Liu, P., Guan, T., Yu, J., Yang, Y.,
Significance-Aware Information Bottleneck for Domain Adaptive Semantic Segmentation,
ICCV19(6777-6786)
IEEE DOI 2004
feature extraction, image classification, image segmentation, neural nets, unsupervised learning, Data mining 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], 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

Zhu, Y.[Yi], Sapra, K.[Karan], Reda, F.A.[Fitsum A.], Shih, K.J.[Kevin J.], Newsam, S.[Shawn], Tao, A.[Andrew], Catanzaro, B.[Bryan],
Improving Semantic Segmentation via Video Propagation and Label Relaxation,
CVPR19(8848-8857).
IEEE DOI 2002
BibRef

Vu, T.H.[Tuan-Hung], Jain, H.[Himalaya], Bucher, M.[Maxime], Cord, M.[Matthieu], Perez, P.[Patrick],
ADVENT: Adversarial Entropy Minimization for Domain Adaptation in Semantic Segmentation,
CVPR19(2512-2521).
IEEE DOI 2002
BibRef

Liu, Y.[Yifan], Chen, K.[Ke], Liu, C.[Chris], Qin, Z.[Zengchang], 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.[Chenguang], Xie, J.[Junyuan],
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], Krešo, I.[Ivan], Oršic, M.[Marin], Šegvic, S.[Siniša],
Simultaneous Semantic Segmentation and Outlier Detection in Presence of Domain Shift,
GCPR19(33-47).
Springer DOI 1911
BibRef

Lin, Y.X.[Yong-Xiang], Tan, D.S.[Daniel Stanley], Cheng, W.H.[Wen-Huang], Chen, Y.Y.[Yung-Yao], Hua, K.L.[Kai-Lung],
Spatially-Aware Domain Adaptation for Semantic Segmentation of Urban Scenes,
ICIP19(1870-1874)
IEEE DOI 1910
Semantic segmentation, Domain adaptation, Spatial Structure 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

Falcão, A.[Alexandre], Bragantini, J.[Jordão],
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

Lv, F.M.[Feng-Mao], Lian, Q.[Qing], Yang, G.[Guowu], Lin, G.S.[Guo-Sheng], Pan, S.J.[Sinno Jialin], Duan, L.X.[Li-Xin],
Domain Adaptive Semantic Segmentation Through Structure Enhancement,
TASKCV18(II:172-179).
Springer DOI 1905
BibRef

Watanabe, K.[Kohei], Saito, K.[Kuniaki], Ushiku, Y.[Yoshitaka], Harada, T.[Tatsuya],
Multichannel Semantic Segmentation with Unsupervised Domain Adaptation,
AutoNUE18(V:600-616).
Springer DOI 1905
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.,
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, Computer vision, Image segmentation 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

Ahn, J.[Jiwoon], Cho, S.[Sunghyun], Kwak, S.[Suha],
Weakly Supervised Learning of Instance Segmentation With Inter-Pixel Relations,
CVPR19(2204-2213).
IEEE DOI 2002
BibRef

Ahn, J.[Jiwoon], Kwak, S.[Suha],
Learning Pixel-Level Semantic Affinity with Image-Level Supervision for Weakly Supervised Semantic Segmentation,
CVPR18(4981-4990)
IEEE DOI 1812
Image segmentation, Semantics, Training, Shape, Visualization, Pipelines, Motion segmentation 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

Huang, P.Y.[Po-Yu], Hsu, W.T.[Wan-Ting], Chiu, C.Y.[Chun-Yueh], Wu, T.F.[Ting-Fan], Sun, M.[Min],
Efficient Uncertainty Estimation for Semantic Segmentation in Videos,
ECCV18(I: 536-552).
Springer DOI 1810
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

Zou, Y.[Yang], Yu, Z.D.[Zhi-Ding], Kumar, B.V.K.V.[B. V. K. Vijaya], Wang, J.S.[Jin-Song],
Unsupervised Domain Adaptation for Semantic Segmentation via Class-Balanced Self-training,
ECCV18(III: 297-313).
Springer DOI 1810
BibRef

Zhu, X.[Xinge], Zhou, H.[Hui], Yang, C.[Ceyuan], 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

Fan, R.C.[Ruo-Chen], Hou, Q.[Qibin], Cheng, M.M.[Ming-Ming], Yu, G.[Gang], Martin, R.R.[Ralph R.], Hu, S.M.[Shi-Min],
Associating Inter-image Salient Instances for Weakly Supervised Semantic Segmentation,
ECCV18(IX: 371-388).
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

Dai, A.[Angela], Nießner, M.[Matthias],
3DMV: Joint 3D-Multi-view Prediction for 3D Semantic Scene Segmentation,
ECCV18(X: 458-474).
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

Xiao, C.W.[Chao-Wei], Deng, R.Z.[Rui-Zhi], Li, B.[Bo], Yu, F.[Fisher], Liu, M.Y.[Ming-Yan], Song, D.[Dawn],
Characterizing Adversarial Examples Based on Spatial Consistency Information for Semantic Segmentation,
ECCV18(X: 220-237).
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
computer vision, image resolution, image segmentation, learning (artificial intelligence), neural nets, LinkNet, Training BibRef

Zhang, Y., Ngan, K.N., Huynh, C.P., Habili, N.,
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

Xie, C., Wang, J., Zhang, Z., Zhou, Y., Xie, L., Yuille, A.L.[Alan L.],
Adversarial Examples for Semantic Segmentation and Object Detection,
ICCV17(1378-1387)
IEEE DOI 1802
image classification, image segmentation, object detection, pattern clustering, adversarial perturbations, Semantics BibRef

Luc, P.[Pauline], Couprie, C.[Camille], Le Cun, Y.[Yann], Verbeek, J.[Jakob],
Predicting Future Instance Segmentation by Forecasting Convolutional Features,
ECCV18(IX: 593-608).
Springer DOI 1810
BibRef

Luc, P.[Pauline], Neverova, N., Couprie, C.[Camille], Verbeek, J.[Jakob], Le Cun, Y.[Yann],
Predicting Deeper into the Future of Semantic Segmentation,
ICCV17(648-657)
IEEE DOI 1802
feedforward neural nets, image colour analysis, image resolution, image segmentation, image sequences, Training 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

Li, Y., Qi, H., Dai, J., Ji, X., Wei, Y.,
Fully Convolutional Instance-Aware Semantic Segmentation,
CVPR17(4438-4446)
IEEE DOI 1711
Convolution, Convolutional codes, Image segmentation, Object segmentation, Proposals, Semantics 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

Bulò, 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

He, Y.[Yang], Chiu, W.C., Keuper, M.[Margret], Fritz, M.[Mario],
STD2P: RGBD Semantic Segmentation Using Spatio-Temporal Data-Driven Pooling,
CVPR17(7158-7167)
IEEE DOI 1711
Image segmentation, Indexes, Optical imaging, Semantics, Training, Videos 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

Namin, S.R., Alvarez, J.M., Petersson, L.,
2D-3D semantic segmentation using cardinality as higher-order loss,
ICPR16(3775-3780)
IEEE DOI 1705
Image edge detection, Image segmentation, Labeling, Sensors, Training. BibRef

Wang, H.L.[Hui-Ling], Raiko, T.[Tapani], Lensu, L.[Lasse], Wang, T.H.[Ting-Huai], Karhunen, J.[Juha],
Semi-supervised Domain Adaptation for Weakly Labeled Semantic Video Object Segmentation,
ACCV16(I: 163-179).
Springer DOI 1704
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.[Lingni], 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

Krapac, J.[Josip], Šegvic, I.K.S.[I.K. Siniša],
Ladder-Style DenseNets for Semantic Segmentation of Large Natural Images,
CVRoads17(238-245)
IEEE DOI 1802
BibRef
Earlier:
Weakly-Supervised Semantic Segmentation by Redistributing Region Scores Back to the Pixels,
GCPR16(377-388).
Springer DOI 1611
Convolution, Image segmentation, Semantics, Spatial resolution, Tensile stress, Training BibRef

Krešo, I.[Ivan], Cauševic, D.[Denis], Krapac, J.[Josip], Šegvic, I.K.S.[I.K. Siniša],
Convolutional Scale Invariance for Semantic Segmentation,
GCPR16(64-75).
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

Samrouth, K., Deforges, O., Liu, Y.[Yi], Falou, W., Khalil, M.,
A joint 3D image semantic segmentation and scalable coding scheme with ROI approach,
VCIP14(270-273)
IEEE DOI 1504
data compression BibRef

Namin, S.T.[Sarah Taghavi], Najafi, M.[Mohammad], Salzmann, M.[Mathieu], Petersson, L.[Lars],
A Multi-modal Graphical Model for Scene Analysis,
WACV15(1006-1013)
IEEE DOI 1503
Graphical models 2D-3D data. Semantic segmentation. 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

Mustikovela, S.K.[Siva Karthik], Yang, M.Y.[Michael Ying], Rother, C.[Carsten],
Can Ground Truth Label Propagation from Video Help Semantic Segmentation?,
VSeg16(III: 804-820).
Springer DOI 1611
BibRef

Zheng, S.[Shuai], Cheng, M.M.[Ming-Ming], Warrell, J.[Jonathan], Sturgess, P.[Paul], Vineet, V.[Vibhav], Rother, C.[Carsten], Torr, P.H.S.[Philip H.S.],
Dense Semantic Image Segmentation with Objects and Attributes,
CVPR14(3214-3221)
IEEE DOI 1409
Attributes; Image Segmentation; Object Recognition; Scene Understanding 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

Chang, F.J.[Feng-Ju], Lin, Y.Y.[Yen-Yu], Hsu, K.J.[Kuang-Jui],
Multiple Structured-Instance Learning for Semantic Segmentation with Uncertain Training Data,
CVPR14(360-367)
IEEE DOI 1409
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

Kundu, A.[Abhijit], Li, Y.[Yin], Dellaert, F.[Frank], Li, F.X.[Fu-Xin], Rehg, J.M.[James M.],
Joint Semantic Segmentation and 3D Reconstruction from Monocular Video,
ECCV14(VI: 703-718).
Springer DOI 1408
BibRef

Inagaki, S.[Shun], Imiya, A.[Atsushi],
Semantic Segmentation of Low Frame-Rate Image Sequence Using Statistical Properties of Optical Flow for Remote Exploration,
ISVC14(I: 477-488).
Springer DOI 1501
BibRef
And:
Statistical Method for Semantic Segmentation of Dominant Plane from Remote Exploration Image Sequence,
SSSPR14(263-272).
Springer DOI 1408
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

Lin, D.[Dahua], Fidler, S.[Sanja], Urtasun, R.[Raquel],
Holistic Scene Understanding for 3D Object Detection with RGBD Cameras,
ICCV13(1417-1424)
IEEE DOI 1403
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

Vezhnevets, A.[Alexander], Ferrari, V.[Vittorio],
Associative Embeddings for Large-Scale Knowledge Transfer with Self-Assessment,
CVPR14(1987-1994)
IEEE DOI 1409
ImageNet BibRef

Vezhnevets, A.[Alexander], Buhmann, J.M.[Joachim M.], Ferrari, V.[Vittorio],
Active learning for semantic segmentation with expected change,
CVPR12(3162-3169).
IEEE DOI 1208
BibRef

Vezhnevets, A.[Alexander], Ferrari, V.[Vittorio], Buhmann, J.M.[Joachim M.],
Weakly supervised structured output learning for semantic segmentation,
CVPR12(845-852).
IEEE DOI 1208
BibRef
Earlier:
Weakly supervised semantic segmentation with a multi-image model,
ICCV11(643-650).
IEEE DOI 1201
BibRef

Vezhnevets, A.[Alexander], Buhmann, J.M.[Joachim M.],
Towards weakly supervised semantic segmentation by means of multiple instance and multitask learning,
CVPR10(3249-3256).
IEEE DOI 1006
See also Agnostic Domain Adaptation. BibRef

Dunlop, H.[Heather],
Scene classification of images and video via semantic segmentation,
POCV10(72-79).
IEEE DOI 1006
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], Leibe, B.[Bastian],
Joint 2D-3D temporally consistent semantic segmentation of street scenes,
CVPR12(2823-2830).
IEEE DOI 1208
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

Micusik, B.[Branislav], Kosecka, J.[Jana],
Semantic segmentation of street scenes by superpixel co-occurrence and 3D geometry,
ObjectEvent09(625-632).
IEEE DOI 0910
identify as one of a few common object/background classes. 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
Fua and Leclerc Guided Segmentation Papers .

Last update:Sep 24, 2020 at 19:44:22