The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
TextonBoost: Joint Appearance, Shape and Context Modeling for Multi-class Object Recognition and Segmentation
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Citations
Cites
Representing and Recognizing the Visual Appearance of Materials Using Three-Dimensional Textons
Leung, T., & Malik, J. (2001) · International Journal of Computer Vision · doi:10.1023/a:1011126920638 · Cited by 1,498 · cited 1×
“For this we utilize textons [17] which have been proven effective in categorizing materials [18] as well as generic object classes [4].”
Method
Cited by
ImageNet: A large-scale hierarchical image database
Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., & Fei-Fei, L. (2009) · 2009 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2009.5206848 · Cited by 65,333
The pascal visual object classes (VOC) challenge
Everingham, M., Van Gool, L., Williams, C. K. I., Winn, J., & Zisserman, A. (2010) · International Journal of Computer Vision · doi:10.1007/s11263-009-0275-4 · Cited by 19,599
Self-citationKirillov, A., Mintun, E., Ravi, N., Mao, H., Rolland, C., Gustafson, L., Xiao, T., Whitehead, S., Berg, A. C., Lo, W.-Y., et al. (2023) · 2023 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.00371 · Cited by 11,953
Learning Hierarchical Features for Scene Labeling
Farabet, C., Couprie, C., Najman, L., & LeCun, Y. (2013) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2012.231 · Cited by 2,620
Relation Networks for Object Detection
Hu, H., Gu, J., Zhang, Z., Dai, J., & Wei, Y. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00378 · Cited by 1,524
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ScribbleSup: Scribble-Supervised Convolutional Networks for Semantic Segmentation
Lin, D., Dai, J., Jia, J., He, K., & Sun, J. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.344 · Cited by 1,129
Segmentation and Recognition Using Structure from Motion Point Clouds
Brostow, G. J., Shotton, J., Fauqueur, J., & Cipolla, R. (2008) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-88682-2_5 · Cited by 1,050
Self-citationAuto-Context and Its Application to High-Level Vision Tasks and 3D Brain Image Segmentation
Tu, Z., & Bai, X. (2010) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2009.186 · Cited by 578
Pixel-Adaptive Convolutional Neural Networks
Su, H., Jampani, V., Sun, D., Gallo, O., Learned-Miller, E., & Kautz, J. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.01142 · Cited by 348
Deep multimodal fusion for semantic image segmentation: A survey
Zhang, Y., Sidibé, D., Morel, O., & Mériaudeau, F. (2021) · Image and Vision Computing · doi:10.1016/j.imavis.2020.104042 · Cited by 261
Discriminative Models for Multi-Class Object Layout
Desai, C., Ramanan, D., & Fowlkes, C. C. (2011) · International Journal of Computer Vision · doi:10.1007/s11263-011-0439-x · Cited by 208
Wang, H., Das, S. R., Suh, J. W., Altinay, M., Pluta, J., Craige, C., Avants, B., & Yushkevich, P. A. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.01.006 · Cited by 177
Deep semantic segmentation for automated driving: Taxonomy, roadmap and challenges
Siam, M., Elkerdawy, S., Jagersand, M., & Yogamani, S. (2017) · 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC) · doi:10.1109/itsc.2017.8317714 · Cited by 178
Regionlets for Generic Object Detection
Wang, X., Yang, M., Zhu, S., & Lin, Y. (2015) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2015.2389830 · Cited by 107
Multi-modal Unsupervised Feature Learning for RGB-D Scene Labeling
Wang, A., Lu, J., Wang, G., Cai, J., & Cham, T.-J. (2014) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-10602-1_30 · Cited by 50
Semantic labeling for prosthetic vision
Horne, L., Alvarez, J., McCarthy, C., Salzmann, M., & Barnes, N. (2016) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2016.02.015 · Cited by 30
A Fusion Model for Road Detection based on Deep Learning and Fully Connected CRF
Yang, F., Yang, J., Jin, Z., & Wang, H. (2018) · 2018 13th Annual Conference on System of Systems Engineering (SoSE) · doi:10.1109/sysose.2018.8428696 · Cited by 13
(2012) · Cited by 4
Metadata
- Authors
- Shotton, J., Winn, J., Rother, C., & Criminisi, A.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2006
- Pages
- 1-15
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W1528789833
- Cited by
- 1,132
- References
- 1
- FWCI
- 52.31
- Type
- conference paper
- Language
- en
- Open access
- closed
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
