8.6.2 Semantic Segmentation, Label and Segment Together

Chapter Contents (Back)
Semantic Segmentation. See also Neural Networks for Segmentation.

Csurka, G.[Gabriela], Perronnin, F.[Florent],
An Efficient Approach to Semantic Segmentation,
IJCV(95), No. 2, November 2011, pp. 198-212.
WWW Link. 1109
BibRef
Earlier:
A Simple High Performance Approach to Semantic Segmentation,
BMVC08(xx-yy).
PDF File. 0809
Assign each pixel to a semantic class. A local appearance model, a local consistency model and a global consistency model. See also Universal and Adapted Vocabularies for Generic Visual Categorization. BibRef

Perronnin, F.[Florent], Dance, C.R.[Christopher R.],
Fisher Kernels on Visual Vocabularies for Image Categorization,
CVPR07(1-8).
IEEE DOI 0706
BibRef
Earlier: Csurka, G.[Gabriela], Bressan, M.[Marco],
Adapted Vocabularies for Generic Visual Categorization,
ECCV06(IV: 464-475).
Springer DOI 0608
BibRef

Csurka, G.[Gabriela], Dance, C.R.[Christopher R.], Perronnin, F.[Florent], Willamowski, J.[Jutta],
Generic Visual Categorization Using Weak Geometry,
CLOR06(207-224).
Springer DOI 0711
BibRef
Earlier: A1, A4, A2, A3:
Incorporating Geometry Information with Weak Classifiers for Improved Generic Visual Categorization,
CIAP05(612-620).
Springer DOI 0509
BibRef

Kemmler, M.[Michael], Rodner, E.[Erik], Wacker, E.S.[Esther-Sabrina], Denzler, J.[Joachim],
One-Class Classification with Gaussian Processes,
PR(46), No. 12, 2013, pp. 3507-3518.
Elsevier DOI 1307
BibRef
Earlier: A1, A2, A4, Only: ACCV10(II: 489-500).
Springer DOI 1011
BibRef
Earlier: A1, A2, A4, Only:
Global Context Extraction for Object Recognition Using a Combination of Range and Visual Features,
Dyn3D09(96-109).
Springer DOI 0909
Combine range and visual, determine general class of scene. One-class classification BibRef

Bodesheim, P.[Paul], Freytag, A.[Alexander], Rodner, E.[Erik], Denzler, J.[Joachim],
Approximations of Gaussian Process Uncertainties for Visual Recognition Problems,
SCIA13(182-194).
Springer DOI 1311
BibRef
Earlier: A1, A3, A2, A4:
Divergence-Based One-Class Classification Using Gaussian Processes,
BMVC12(50).
DOI Link 1301
See also Classification of Microorganisms via Raman Spectroscopy Using Gaussian Processes. BibRef

Käding, C.[Christoph], Freytag, A.[Alexander], Rodner, E.[Erik], Perino, A.[Andrea], Denzler, J.[Joachim],
Large-Scale Active Learning with Approximations of Expected Model Output Changes,
GCPR16(179-191).
Springer DOI 1611
BibRef

Freytag, A.[Alexander], Rodner, E.[Erik], Denzler, J.[Joachim],
Selecting Influential Examples: Active Learning with Expected Model Output Changes,
ECCV14(IV: 562-577).
Springer DOI 1408
BibRef

Rodner, E.[Erik], Freytag, A.[Alexander], Bodesheim, P.[Paul], Fröhlich, B.[Björn], Denzler, J.[Joachim],
Large-Scale Gaussian Process Inference with Generalized Histogram Intersection Kernels for Visual Recognition Tasks,
IJCV(121), No. 2, January 2017, pp. 253-280.
Springer DOI 1702
BibRef

Freytag, A.[Alexander], Rodner, E.[Erik], Bodesheim, P.[Paul], Denzler, J.[Joachim],
Labeling Examples That Matter: Relevance-Based Active Learning with Gaussian Processes,
GCPR13(282-291).
Springer DOI 1311
BibRef
Earlier:
Rapid Uncertainty Computation with Gaussian Processes and Histogram Intersection Kernels,
ACCV12(II:511-524).
Springer DOI 1304
BibRef

Freytag, A.[Alexander], Frohlich, B.[Bjorn], Rodner, E.[Erik], Denzler, J.[Joachim],
Efficient semantic segmentation with Gaussian processes and histogram intersection kernels,
ICPR12(3313-3316).
WWW Link. 1302
BibRef

Rodner, E.[Erik], Freytag, A.[Alexander], Bodesheim, P.[Paul], Denzler, J.[Joachim],
Large-Scale Gaussian Process Classification with Flexible Adaptive Histogram Kernels,
ECCV12(IV: 85-98).
Springer DOI 1210
BibRef

Rodner, E.[Erik], Hegazy, D., Denzler, J.[Joachim],
Multiple kernel Gaussian process classification for generic 3D object recognition,
IVCNZ10(1-8).
IEEE DOI 1203
BibRef

Pei, D.L.[De-Li], Li, Z.G.[Zhen-Guo], Ji, R.R.[Rong-Rong], Sun, F.C.[Fu-Chun],
Efficient semantic image segmentation with multi-class ranking prior,
CVIU(120), No. 1, 2014, pp. 81-90.
Elsevier DOI 1403
Computer vision BibRef

Osuna-Enciso, V.[Valentín],
Bioinspired metaheuristics for image segmentation,
ELCVIA(13), No. 2, 2014, pp. xx-yy.
WWW Link. 1407
Ph.D.. Thesis. BibRef

Wang, L.[Le], Hua, G.[Gang], Xue, J.R.[Jian-Ru], Gao, Z.N.[Zhan-Ning], Zheng, N.N.[Nan-Ning],
Joint Segmentation and Recognition of Categorized Objects From Noisy Web Image Collection,
IP(23), No. 9, September 2014, pp. 4070-4086.
IEEE DOI 1410
image retrieval BibRef

Gould, S.[Stephen], He, X.M.[Xu-Ming],
Scene Understanding by Labeling Pixels,
CACM(57), No. 11, November 2014, pp. 68-77.
DOI Link 1411
Pixels labeled with a scene's semantics and geometry let computers describe what they see. BibRef

Liu, Z.[Zhi], Xu, S.Q.[Shu-Qiong], Zhang, Y.[Yun], Chen, C.L.P.,
A Multiple-Feature and Multiple-Kernel Scene Segmentation Algorithm for Humanoid Robot,
Cyber(44), No. 11, November 2014, pp. 2232-2241.
IEEE DOI 1411
Gabor filters BibRef

Kang, H., Hebert, M., Efros, A.A., Kanade, T.,
Data-Driven Objectness,
PAMI(37), No. 1, January 2015, pp. 189-195.
IEEE DOI 1412
Databases. Is it an object, not a specific object. BibRef

Wang, L.L.[Li-Li], Yung, N.H.C.[Nelson H.C.],
Hybrid graphical model for semantic image segmentation,
JVCIR(28), No. 1, 2015, pp. 83-96.
Elsevier DOI 1503
Semantic segmentation BibRef

Wang, L.L.[Li-Li], Yung, N.H.C.[Nelson H. C.],
Improved hierarchical conditional random field model for object segmentation,
MVA(26), No. 7-8, November 2015, pp. 1027-1043.
WWW Link. 1511
BibRef

Xia, W.[Wei], Domokos, C.[Csaba], Cheong, L.F.[Loong-Fah], Yan, S.C.[Shui-Cheng],
Background Context Augmented Hypothesis Graph for Object Segmentation,
CirSysVideo(25), No. 4, April 2015, pp. 582-594.
IEEE DOI 1504
Context BibRef

Xia, W.[Wei], Domokos, C.[Csaba], Xiong, J., Cheong, L.F.[Loong-Fah], Yan, S.C.[Shui-Cheng],
Segmentation Over Detection via Optimal Sparse Reconstructions,
CirSysVideo(25), No. 8, August 2015, pp. 1295-1308.
IEEE DOI 1508
Bismuth BibRef

Xia, W.[Wei], Domokos, C.[Csaba], Dong, J.[Jian], Cheong, L.F.[Loong-Fah], Yan, S.C.[Shui-Cheng],
Semantic Segmentation without Annotating Segments,
ICCV13(2176-2183)
IEEE DOI 1403
Given object bounding box. BibRef

Kumar, M.P., Turki, H., Preston, D., Koller, D.,
Parameter Estimation and Energy Minimization for Region-Based Semantic Segmentation,
PAMI(37), No. 7, July 2015, pp. 1373-1386.
IEEE DOI 1506
Biological system modeling BibRef

Korner, M.[Marco], Krishna, M.V.[Mahesh V.], Susse, H.[Herbert], Ortmann, W.[Wolfang], Denzler, J.[Joachim],
Regularized Geometric Hulls for Bio-medical Image Segmentation,
BMVA(2015), No. 4, 2015, pp. 1-12.
PDF File. 1509
BibRef

Mottaghi, R.[Roozbeh], Fidler, S.[Sanja], Yuille, A.L., Urtasun, R.[Raquel], Parikh, D.[Devi],
Human-Machine CRFs for Identifying Bottlenecks in Scene Understanding,
PAMI(38), No. 1, January 2016, pp. 74-87.
IEEE DOI 1601
Analytical models BibRef

Mottaghi, R.[Roozbeh], Fidler, S.[Sanja], Yao, J.[Jian], Urtasun, R.[Raquel], Parikh, D.[Devi],
Analyzing Semantic Segmentation Using Hybrid Human-Machine CRFs,
CVPR13(3143-3150)
IEEE DOI 1309
Explore effects by using humans in loop for parts of the problem. BibRef

Ravě, D., Bober, M., Farinella, G.M., Guarnera, M., Battiato, S.,
Semantic segmentation of images exploiting DCT based features and random forest,
PR(52), No. 1, 2016, pp. 260-273.
Elsevier DOI 1601
Semantic segmentation BibRef

Tung, F.[Frederick], Little, J.J.[James J.],
Scene parsing by nonparametric label transfer of content-adaptive windows,
CVIU(143), No. 1, 2016, pp. 191-200.
Elsevier DOI 1601
BibRef
Earlier:
CollageParsing: Nonparametric Scene Parsing by Adaptive Overlapping Windows,
ECCV14(VI: 511-525).
Springer DOI 1408
Image parsing BibRef

Zarchi, M.S., Tan, R.T., van Gemeren, C.[Coert], Monadjemi, A., Veltkamp, R.C.[Remco C.],
Understanding image concepts using ISTOP model,
PR(53), No. 1, 2016, pp. 174-183.
Elsevier DOI 1602
Visual term. Image parsing. BibRef

Jiang, J., Song, X.,
An Optimized Higher Order CRF for Automated Labeling and Segmentation of Video Objects,
CirSysVideo(26), No. 3, March 2016, pp. 506-516.
IEEE DOI 1603
Color BibRef

Diebold, J.[Julia], Nieuwenhuis, C.[Claudia], Cremers, D.[Daniel],
Midrange Geometric Interactions for Semantic Segmentation,
IJCV(117), No. 3, May 2016, pp. 199-225.
Springer DOI 1605
See also Convex Optimization for Scene Understanding. See also Proximity Priors for Variational Semantic Segmentation and Recognition. BibRef

Nieuwenhuis, C.[Claudia], Strekalovskiy, E.[Evgeny], Cremers, D.[Daniel],
Proportion Priors for Image Sequence Segmentation,
ICCV13(2328-2335)
IEEE DOI 1403
BibRef
Earlier: A2, A1, A3:
Nonmetric Priors for Continuous Multilabel Optimization,
ECCV12(VII: 208-221).
Springer DOI 1210
BibRef

Hazirbas, C.[Caner], Diebold, J.[Julia], Cremers, D.[Daniel],
Optimizing the Relevance-Redundancy Tradeoff for Efficient Semantic Segmentation,
SSVM15(243-255).
Springer DOI 1506
BibRef

Zand, M., Doraisamy, S., Halin, A.A.[A. Abdul], Mustaffa, M.R.,
Ontology-Based Semantic Image Segmentation Using Mixture Models and Multiple CRFs,
IP(25), No. 7, July 2016, pp. 3233-3248.
IEEE DOI 1606
image segmentation BibRef

Pont-Tuset, J.[Jordi], Arbeláez, P.[Pablo], Barron, J.T.[Jon T.], Marques, F.[Ferran], Malik, J.[Jitendra],
Multiscale Combinatorial Grouping for Image Segmentation and Object Proposal Generation,
PAMI(39), No. 1, January 2017, pp. 128-140.
IEEE DOI 1612
BibRef
Earlier: A2, A1, A3, A4, A5:
Multiscale Combinatorial Grouping,
CVPR14(328-335)
IEEE DOI 1409
Detectors. Image Segmentation; Object Candidates BibRef

Hariharan, B.[Bharath], Arbeláez, P.[Pablo], Girshick, R.[Ross], Malik, J.[Jitendra],
Simultaneous Detection and Segmentation,
ECCV14(VII: 297-312).
Springer DOI 1408
See also Indoor Scene Understanding with RGB-D Images: Bottom-up Segmentation, Object Detection and Semantic Segmentation. BibRef

Arbelaez, P.[Pablo], Hariharan, B.[Bharath], Gu, C.H.[Chun-Hui], Gupta, S.[Saurabh], Bourdev, L.[Lubomir], Malik, J.[Jitendra],
Semantic segmentation using regions and parts,
CVPR12(3378-3385).
IEEE DOI 1208
BibRef

Shelhamer, E.[Evan], Long, J.[Jonathan], Darrell, T.J.[Trevor J.],
Fully Convolutional Networks for Semantic Segmentation,
PAMI(39), No. 4, April 2017, pp. 640-651.
IEEE DOI 1703
BibRef
Earlier: A2, A1, A3: CVPR15(3431-3440)
IEEE DOI 1510
Award, CVPR, HM. Computer architecture BibRef

Shelhamer, E.[Evan], Rakelly, K.[Kate], Hoffman, J.[Judy], Darrell, T.J.[Trevor J.],
Clockwork Convnets for Video Semantic Segmentation,
VSeg16(III: 852-868).
Springer DOI 1611
BibRef

Li, Y., Guo, Y., Kao, Y., He, R.,
Image Piece Learning for Weakly Supervised Semantic Segmentation,
SMCS(47), No. 4, April 2017, pp. 648-659.
IEEE DOI 1704
Correlation BibRef

Wang, L.T.[Lian-Tao], Meng, D., Hu, X.L.[Xue-Lei], Lu, J.F.[Jian-Feng], Zhao, J.[Ji],
Instance Annotation via Optimal BoW for Weakly Supervised Object Localization,
Cyber(47), No. 5, May 2017, pp. 1313-1324.
IEEE DOI 1704
BibRef
Earlier: A1, A5, A3, A4, Only:
Weakly supervised object localization via maximal entropy randomwalk,
ICIP14(1614-1617)
IEEE DOI 1502
Birds. Entropy BibRef

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

Liu, Y.[Yu], Nguyen, D.M.[Duc Minh], Deligiannis, N.[Nikos], Ding, W.[Wenrui], Munteanu, A.[Adrian],
Hourglass-Shape Network Based Semantic Segmentation for High Resolution Aerial Imagery,
RS(9), No. 6, 2017, pp. xx-yy.
DOI Link 1706
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

Badrinarayanan, V.[Vijay], Kendall, A.[Alex], Cipolla, R.[Roberto],
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation,
PAMI(39), No. 12, December 2017, pp. 2481-2495.
IEEE DOI 1711
Convolutional codes, Decoding, Image segmentation, Neural networks, Semantics, Training, indoor scenes, pooling, road scenes, semantic pixel-wise segmentation, upsampling 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

Larsson, M.[Mĺns], Alvén, J.[Jennifer], Kahl, F.[Fredrik],
Max-Margin Learning of Deep Structured Models for Semantic Segmentation,
SCIA17(II: 28-40).
Springer DOI 1706
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, Three-dimensional displays, Training, Two, dimensional, displays 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

Audebert, N.[Nicolas], Le Saux, B.[Bertrand], Lefčvre, S.[Sébastien],
Joint Learning from Earth Observation and OpenStreetMap Data to Get Faster Better Semantic Maps,
EarthVision17(1552-1560)
IEEE DOI 1709
BibRef
Earlier:
Semantic Segmentation of Earth Observation Data Using Multimodal and Multi-scale Deep Networks,
ACCV16(I: 180-196).
Springer DOI 1704
Buildings, Labeling, Optical imaging, Roads, Semantics, Sensors, Training 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

Hong, S., Oh, J., Lee, H., Han, B.,
Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network,
CVPR16(3204-3212)
IEEE DOI 1612
BibRef

Lin, G., Shen, C., van den Hengel, A.J.[Anton J.], Reid, I.D.,
Efficient Piecewise Training of Deep Structured Models for Semantic Segmentation,
CVPR16(3194-3203)
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

Qi, G.J.[Guo-Jun],
Hierarchically Gated Deep Networks for Semantic Segmentation,
CVPR16(2267-2275)
IEEE DOI 1612
BibRef

Li, K.[Ke], Malik, J.[Jitendra],
Amodal Instance Segmentation,
ECCV16(II: 677-693).
Springer DOI 1611
predict the region encompassing both visible and occluded parts of each object. 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

Shimoda, W.[Wataru], Yanai, K.[Keiji],
Distinct Class-Specific Saliency Maps for Weakly Supervised Semantic Segmentation,
ECCV16(IV: 218-234).
Springer DOI 1611
BibRef

Saleh, F.[Fatemehsadat], Aliakbarian, M.S.[Mohammad Sadegh], Salzmann, M.[Mathieu], Petersson, L.[Lars], Gould, S.[Stephen], Alvarez, J.M.[Jose M.],
Built-in Foreground/Background Prior for Weakly-Supervised Semantic Segmentation,
ECCV16(VIII: 413-432).
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, S.[Siniša],
Weakly-Supervised Semantic Segmentation by Redistributing Region Scores Back to the Pixels,
GCPR16(377-388).
Springer DOI 1611
BibRef

Krešo, I.[Ivan], Cauševic, D.[Denis], Krapac, J.[Josip], Šegvic, S.[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

Ran, L.Y.[Ling-Yan], Zhang, Y.N.[Yan-Ning], Hua, G.[Gang],
CANNET: Context aware nonlocal convolutional networks for semantic image segmentation,
ICIP15(4669-4673)
IEEE DOI 1512
Semantic segmentation; context aware module; sparse kernel 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

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

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

Li, K.[Ke], Hariharan, B.[Bharath], Malik, J.[Jitendra],
Iterative Instance Segmentation,
CVPR16(3659-3667)
IEEE DOI 1612
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:Nov 11, 2017 at 13:31:57