8.6.3.8 Efficient Semantic Segmentation, Real-Time Segmentation

Chapter Contents (Back)
Semantic Segmentation. Efficient Segmentation. Real-Time 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

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

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

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

Choi, H.[Hyunguk], Ahn, H.[Hoyeon], Kim, J.[Joonmo], Jeon, M.[Moongu],
ADFNet: Accumulated decoder features for real-time semantic segmentation,
IET-CV(14), No. 8, December 2020, pp. 555-563.
DOI Link 2012
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

Mohan, R.[Rohit], Valada, A.[Abhinav],
EfficientPS: Efficient Panoptic Segmentation,
IJCV(129), No. 5, May 2021, pp. 1551-1579.
Springer DOI 2105
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

Oršic, M.[Marin], Šegvic, S.[Siniša],
Efficient semantic segmentation with pyramidal fusion,
PR(110), 2021, pp. 107611.
Elsevier DOI 2011
Semantic segmentation, Real-time inference, Shared resolution pyramid, Deep learning BibRef

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

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

Tan, Z.T.[Zhen-Tao], Chen, D.D.[Dong-Dong], Chu, Q.[Qi], Chai, M.L.[Meng-Lei], Liao, J.[Jing], He, M.M.[Ming-Ming], Yuan, L.[Lu], Hua, G.[Gang], Yu, N.H.[Neng-Hai],
Efficient Semantic Image Synthesis via Class-Adaptive Normalization,
PAMI(44), No. 9, September 2022, pp. 4852-4866.
IEEE DOI 2208
Semantics, Image synthesis, Modulation, Image segmentation, Task analysis, Generators, Visualization, Semantic image synthesis, Positional encoding BibRef

Weng, X.[Xi], Yan, Y.[Yan], Chen, S.[Si], Xue, J.H.[Jing-Hao], Wang, H.Z.[Han-Zi],
Stage-Aware Feature Alignment Network for Real-Time Semantic Segmentation of Street Scenes,
CirSysVideo(32), No. 7, July 2022, pp. 4444-4459.
IEEE DOI 2207
Semantics, Decoding, Real-time systems, Image segmentation, Training, Aggregates, Predictive models, Real-time semantic segmentation, feature alignment and aggregation 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 BibRef

Weng, X.[Xi], Yan, Y.[Yan], Dong, G.S.[Gen-Shun], Shu, C.[Chang], Wang, B.[Biao], Wang, H.Z.[Han-Zi], Zhang, J.[Ji],
Deep Multi-Branch Aggregation Network for Real-Time Semantic Segmentation in Street Scenes,
ITS(23), No. 10, October 2022, pp. 17224-17240.
IEEE DOI 2210
Semantics, Real-time systems, Image segmentation, Lattices, Decoding, Task analysis, Feature extraction, Deep learning, multi-branch aggregation BibRef

Rosas-Arias, L.[Leonel], Benitez-Garcia, G.[Gibran], Portillo-Portillo, J.[José], Olivares-Mercado, J.[Jesus], Sánchez-Pérez, G.[Gabriel], Yanai, K.[Keiji],
FASSD-Net: Fast and Accurate Real-Time Semantic Segmentation for Embedded Systems,
ITS(23), No. 9, September 2022, pp. 14349-14360.
IEEE DOI 2209
BibRef
Earlier: A1, A2, A3, A5, A6, Only:
Fast and Accurate Real-Time Semantic Segmentation with Dilated Asymmetric Convolutions,
ICPR21(2264-2271)
IEEE DOI 2105
Real-time systems, Semantics, Convolutional codes, Embedded systems, Decoding, Task analysis, Image segmentation. Convolutional codes, Image resolution, Quantization (signal), Real-time systems BibRef

Verelst, T.[Thomas], Tuytelaars, T.[Tinne],
SegBlocks: Block-Based Dynamic Resolution Networks for Real-Time Segmentation,
PAMI(45), No. 2, February 2023, pp. 2400-2411.
IEEE DOI 2301
Image segmentation, Complexity theory, Task analysis, Computational efficiency, Semantics, Computational modeling, Costs, semantic segmentation BibRef

Seifi, S.[Soroush], Tuytelaars, T.[Tinne],
Attend and Segment: Attention Guided Active Semantic Segmentation,
ECCV20(XXV:305-321).
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

Xu, G.P.[Guo-Ping], Liao, W.T.[Wen-Tao], Zhang, X.[Xuan], Li, C.[Chang], He, X.W.[Xin-Wei], Wu, X.L.[Xing-Long],
Haar wavelet downsampling: A simple but effective downsampling module for semantic segmentation,
PR(143), 2023, pp. 109819.
Elsevier DOI 2310
Semantic segmentation, Downsampling, Haar wavelet, Information entropy BibRef

Guo, Z.[Zibo], Liu, K.[Kai], Liu, W.[Wei], Sun, X.Y.[Xiao-Yao], Ding, C.Y.[Chong-Yang], Li, S.R.[Shang-Rong],
An Overlay Accelerator of DeepLab CNN for Spacecraft Image Segmentation on FPGA,
RS(16), No. 5, 2024, pp. 894.
DOI Link 2403
BibRef


Li, Y.[Yuan], Hu, T.T.[Ting-Ting], Fuchikami, R.[Ryuji], Ikenaga, T.[Takeshi],
Grid Sample Based Temporal Iteration and Compactness-coefficient Distance for High Frame and Ultra-low Delay SLIC Segmentation System,
MVA23(1-5)
DOI Link 2403
High frame rate video. Image segmentation, Object segmentation, Power system stability, Delays, Robots, Manufacturing automation, Videos BibRef

Chen, J.[Jiakun], Wei, Y.[Yan], Xie, Y.[Yu],
Combining attention mechanism and Feature Selection Module for Real-time semantic segmentation,
CVIDL23(334-337)
IEEE DOI 2403
Training, Solid modeling, Semantic segmentation, Computational modeling, Neural networks, Feature extraction, activation function BibRef

Liu, B.[Bing], Chen, C.[Chen], Bao, X.L.[Xue-Liang], Zhong, Z.H.[Zhao-Hao],
PSDFormer: A Pyramid Simple Detail Injection Transformer for Real Time Semantic Segmentation,
CVIDL23(296-299)
IEEE DOI 2403
Deep learning, Head, Fuses, Semantic segmentation, Semantics, Computer architecture, real-time, semantic segmentation, autonomous driving BibRef

Yang, C.[Changdi], Zhao, P.[Pu], Li, Y.[Yanyu], Niu, W.[Wei], Guan, J.X.[Jie-Xiong], Tang, H.[Hao], Qin, M.H.[Ming-Hai], Ren, B.[Bin], Lin, X.[Xue], Wang, Y.Z.[Yan-Zhi],
Pruning Parameterization with Bi-level Optimization for Efficient Semantic Segmentation on the Edge,
CVPR23(15402-15412)
IEEE DOI 2309
BibRef

Hu, Y.[Yubin], He, Y.Z.[Yu-Ze], Li, Y.H.[Yang-Hao], Li, J.S.[Ji-Sheng], Han, Y.X.[Yu-Xing], Wen, J.T.[Jiang-Tao], Liu, Y.J.[Yong-Jin],
Efficient Semantic Segmentation by Altering Resolutions for Compressed Videos,
CVPR23(22627-22637)
IEEE DOI 2309
BibRef

Lu, C.Y.[Chen-Yang], de Geus, D.[Daan], Dubbelman, G.[Gijs],
Content-aware Token Sharing for Efficient Semantic Segmentation with Vision Transformers,
CVPR23(23631-23640)
IEEE DOI 2309
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

Dong, J.[Jianan], Guo, J.[Jichang], Yue, H.H.[Hui-Hui], Gao, H.[Huan],
EANET: Efficient Attention-Augmented Network for Real-Time Semantic Segmentation,
ICIP22(3968-3972)
IEEE DOI 2211
Strips, Costs, Semantics, Graphics processing units, Real-time systems, Mobile handsets, Task analysis, Multi-level Features BibRef

Mehta, D.[Dushyant], Skliar, A.[Andrii], Ben Yahia, H.[Haitam], Borse, S.[Shubhankar], Porikli, F.M.[Fatih M.], Habibian, A.[Amirhossein], Blankevoort, T.[Tijmen],
Simple and Efficient Architectures for Semantic Segmentation,
ECV22(2627-2635)
IEEE DOI 2210
Image segmentation, Head, Semantics, Graphics processing units, Computer architecture, Hardware, Distance measurement 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

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

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

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

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

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

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

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

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

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

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

Zhao, H.S.[Heng-Shuang], 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

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

Li, W.H.[Wei-Hao], 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

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

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

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

Chapter on 2-D Region Segmentation Techniques, Snakes, Active Contours continues in
Fua and Leclerc Guided Segmentation Papers .


Last update:May 6, 2024 at 15:50:14