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Publications |
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1. |
Chieh Liu, Yu-Min Chu, Ting-I Hsieh, Hwann-Tzong Chen and Tyng-Luh Liu, "Learning Diffusion Models for Multi-View Anomaly Detection," 18th European Conference on Computer Vision (ECCV), Milan, Italy, 2024, (ECCV) |
2. |
Chih-Jung Tsai, Hwann-Tzong Chen and Tyng-Luh Liu, "Pseudo-Embedding for Generalized Few-Shot 3D Segmentation," 18th European Conference on Computer Vision (ECCV), Milan, Italy, 2024, (ECCV) |
3. |
Pei-Kai Huang, Cheng-Hsuan Chiang, Tzu-Hsien Chen, Jun-Xiong Chong, Tyng-Luh Liu and Chiou-ting Hsu, "One-Class Face Anti-spoofing via Spoof Cue Map-Guided Feature Learning," IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024, (CVPR) |
4. |
Cheng-Yao Hong, Yen-Chi Hsu and Tyng-Luh Liu, "Contrastive Learning for DeepFake Classification and Localization via Multi-Label Ranking," IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, USA, 2024, (CVPR) |
5. |
Yu-Min Chu, Chieh Liu, Ting-I Hsieh, Hwann-Tzong Chen and Tyng-Luh Liu, "Shape-Guided Dual-Memory Learning for 3D Anomaly Detection," 40th International Conference on Machine Learning, Hawaii, USA, 2023, (ICML) |
6. |
Cheng-Yao Hong, Yu-Ying Chou and Tyng-Luh Liu, "Attention Discriminant Sampling for Point Clouds," International Conference on Computer Vision, Paris, France, 2023, (ICCV) |
7. |
Yen-Chi Hsu, Cheng-Yao Hong, Ming-Sui Lee, Davi Geiger and Tyng-Luh Liu, "ABC-Norm Regularization for Fine-Grained and Long-Tailed Image Classification," IEEE Transactions on Image Processing, volume 32, pages 3885-3896, July 2023, (TIP) |
8. |
He-Yen Hsieh, Ding-Jie Chen, Cheng-Wei Chang and Tyng-Luh Liu, "One-shot Action Detection via Attention Zooming In," IEEE International Conference on Acoustics, Speech and Signal Processing, Rhodes Island, Greece, June 2023, (ICASSP) |
9. |
Wan-Cyuan Fan, Cheng-Yao Hong, Yen-Chi Hsu and Tyng-Luh Liu, "IoU-Aware Multi-Expert Cascade Network via Dynamic Ensemble for Long-tailed Object Detection," IEEE International Conference on Acoustics, Speech and Signal Processing, Rhodes Island, Greece, June 2023, (ICASSP) |
10. |
He-Yen Hsieh, Ding-Jie Chen, Cheng-Wei Chang and Tyng-Luh Liu, "Aggregating Bilateral Attention for Few-Shot Instance Localization," Winter Conference on Applications of Computer Vision, Hawaii, USA, January 2023, (WACV) |
11. |
Jhih-Ciang Wu, He-Yen Hsieh, Ding-Jie Chen, Chiou-Shann Fuh and Tyng-Luh Liu, "Self-Supervised Sparse Representation for Video Anomaly Detection," 17th European Conference on Computer Vision, Tel-Aviv, Israel, October 2022, (ECCV) |
12. |
Chun-Hsiao Yeh, Cheng-Yao Hong, Yen-Chi Hsu, Tyng-Luh Liu, Yubei Chen and Yann LeCun, "Decoupled Contrastive Learning," 17th European Conference on Computer Vision, Tel-Aviv, Israel, October 2022, (ECCV) |
13. |
Robert Kaderka, Keng-Chi Liu, Lawrence Liu, Reynald VanderStraeten, Tyng-Luh Liu, Kuang-Min Lee, Yi-Chin Ethan Tu, Iain MacEwan, Daniel Simpson, James Urbanic and Chang Chang, "Toward Automatic Beam Angle Selection for Pencil-Beam Scanning Proton Liver Treatments: A Deep Learning–based Approach," Medical Physics, volume 49, number 7, pages 4293-4304, July 2022, (Editor's Choice) |
14. |
Wen-Li Wei, Jen-Chun Lin, Tyng-Luh Liu, and Hong-Yuan Mark Liao, "Capturing Humans in Motion: Temporal-Attentive 3D Human Pose and Shape Estimation from Monocular Video," IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), June 2022. ::: |
15. |
Chun-Hsiao Yeh, Cheng-Yao Hong, Yen-Chi Hsu and Tyng-Luh Liu, "SAGA: Self-Augmentation with Guided Attention for Representation Learning," 2022 IEEE International Conference on Acoustics, Speech and Signal Processing, May 2022, (ICASSP) |
16. |
Ta-Ying Cheng, Hsuan-ru Yang, Niki Trigoni, Hwann-Tzong Chen and Tyng-Luh Liu, "Pose Adaptive Dual Mixup for Few-Shot Single-View 3D Reconstruction," Thirty-Sixth AAAI Conference on Artificial Intelligence, February 2022, (AAAI) |
17. |
He-Yen Hsieh , Ding-Jie Chen, and Tyng-Luh Liu, "Contextual Proposal Network for Action Localization," Winter Conference on Applications of Computer Vision, January 2022, (WACV) |
18. |
Jun-Liang Lin, Tsung-Ting Hsieh, Yi-An Tung, Xuan-Jun Chen, Yu-Chun Hsiao, Chia-Lin Yang, Tyng-Luh Liu and Chien-Yu Chen, "ezGeno: An Automatic Model Selection Package for Genomic Data Analysis," Bioinformatics, volume 38, number 1, pages 30-37, January 2022. |
19. |
Lung-Wen Tsai, Kuo-Ching Yuan, Sen-Kuang Hou, Wei-Lin Wu, Chen-Hao Hsu, Tyng-Luh Liu, Kuang-Min Lee, Chiao-Hsuan Li, Hann-Chyun Chen, Ethan Tu, Rajni Dubey, Chun-Fu Yeh and Ray-Jade Chen, "Determining Carina and Clavicular Distance-Dependent Positioning of Endotracheal Tube in Critically Ill Patients: An Artificial Intelligence-Based Approach," Biology, volume 11, number 4, 2022. |
20. |
Jhih-Ciang Wu, Ding-Jie Chen, Chiou-Shann Fuh and Tyng-Luh Liu, "Learning Unsupervised Metaformer for Anomaly Detection," International Conference on Computer Vision, October 2021, (ICCV) |
21. |
Jhih-Ciang Wu, Sherman Lu, Chiou-Shann Fuh and Tyng-Luh Liu, "One-Class Anomaly Detection via Novelty Normalization," Computer Vision and Image Understanding, volume 210, pages 103226, September 2021. |
22. |
Jun-Liang Lin, Yi-Lin Sung, Cheng-Yao Hong, Han-Hung Lee and Tyng-Luh Liu, "The Maximum a Posteriori Estimation of DARTS," IEEE International Conference on Image Processing, Anchorage, Alaska, USA, September 2021. |
23. |
Ding-Jie Chen, He-Yen Hsieh and Tyng-Luh Liu, "Adaptive Image Transformer for One-Shot Object Detection," IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 2021, (CVPR) |
24. |
Ding-Jie Chen, He-Yen Hsieh and Tyng-Luh Liu, "Referring Image Segmentation via Language-Driven Attention," International Conference on Robotics and Automation, May 2021, (ICRA) |
25. |
Yu-Ying Chou, Hsuan-Tien Lin and Tyng-Luh Liu, "Adaptive and Generative Zero-Shot Learning," Ninth International Conference on Learning Representations, May 2021, (ICLR) |
26. |
Pin-Hao Huang, Han-Hung Lee, Hwann-Tzong Chen and Tyng-Luh Liu, "Text-guided Graph Neural Networks for Referring 3D Instance Segmentation," Thirty-Fifth AAAI Conference on Artificial Intelligence, February 2021, (AAAI) |
27. |
Wen-Li Wei, Jen-Chun Lin, Tyng-Luh Liu, Hsiao-Rong Tyan, Hsin-Min Wang and Hong-Yuan Mark Liao, "Learning to Visualize Music Through Shot Sequence for Automatic Concert Video Mashup," IEEE Transactions on Multimedia, volume 23, pages 1731-1743, 2021. |
28. |
Jen-Chun Lin, Wen-Li Wei, Yen-Yu Lin, Tyng-Luh Liu, and Hong-Yuan Mark Liao, "Learning From Music to Visual Storytelling of Shots: A Deep Interactive Learning Mechanism," ACM Multimedia Conference, Online (Seattle, USA), October 2020, (ACM MM) |
29. |
Yi-Lin Sung, Cheng-Yao Hong, Yen-Chi Hsu, and Tyng-Luh Liu, "Video Summarization with Anchors and Multi-head Attention," IEEE International Conference on Image Processing, Online (United Arab Emirates), October 2020. |
30. |
He-Yen Hsieh, Ding-Jie Chen, and Tyng-Luh Liu, "Temporal Action Proposal Generation via Deep Feature Enhancement," IEEE International Conference on Image Processing, Online (United Arab Emirates), October 2020. |
31. |
Hsien-Tzu Cheng, Chun-Fu Yeh, Po-Chen Kuo, Andy Wei, Keng-Chi Liu, Mong-Chi Ko, Kuan-Hua Chao, Yu-Ching Peng, and Tyng-Luh Liu, "Self-similarity Student for Partial Label Histopathology Image Segmentation," 16th European Conference on Computer Vision, Springer, Online, August 2020, (ECCV) |
32. |
Chun-Fu Yeh, Hsien-Tzu Cheng, Andy Wei, Hsin-Ming Chen, Po-Chen Kuo, Keng-Chi Liu, Mong-Chi Ko, Ray-Jade Chen, Po-Chang Lee, Jen-Hsiang Chuang, Chi-Mai Chen, Yi-Chang Chen, Wen-Jeng Lee, Ning Chien, Jo-Yu Chen, Yu-Sen Huang, Yu-Chien Chang, Yu-Cheng Huang, Nai-Kuan Chou, Kuan-Hua Chao, Yi-Chin Tu, Yeun-Chung Chang and Tyng-Luh Liu, "A Cascaded Learning Strategy for Robust COVID-19 Pneumonia Chest X-Ray Screening," arXiv:2004.12786, April 2020. |
33. |
Yen-Chi Hsu, Cheng-Yao Hong, Ming-Sui Lee and Tyng-Luh Liu, "Query-Driven Multi-Instance Learning," Thirty-Fourth AAAI Conference on Artificial Intelligence, February 2020, (AAAI) ::: |
34. |
Ting-I Hsieh, Yi-Chen Lo, Hwann-Tzong Chen, and Tyng-Luh Liu, "One-Shot Object Detection with Co-Attention and Co-Excitation," Thirty-third Conference on Neural Information Processing Systems, December 2019, (NeurIPS) ::: |
35. |
Jen-Chun Lin, Wen-Li Wei, Tyng-Luh Liu, C.-C. Jay Kuo and Mark Liao, "Tell Me Where It is Still Blurry: Adversarial Blurred Region Mining and Refining," ACM Multimedia Conference, October 2019, (ACM MM) ::: |
36. |
Ding-Jie Chen, Songhao Jia, Yi-Chen Lo, Hwann-Tzong Chen, and Tyng-Luh Liu, "See-through-Text Grouping for Referring Image Segmentation," International Conference on Computer Vision, October 2019, (ICCV) ::: |
37. |
Chih-Yao Chiu, Hwann-Tzong Chen and Tyng-Luh Liu, "C2S2: Cost-aware Channel Sparse Selection for Progressive Network Pruning," arXiv:1904.03508, April 2019. |
38. |
Ding-Jie Chen, Jui-Ting Chien, Hwann-Tzong Chen, and Tyng-Luh Liu, "Unsupervised Meta-learning of Figure-Ground Segmentation via Imitating Visual Effects," Thirty-Third AAAI Conference on Artificial Intelligence, January 2019, (AAAI) ::: |
39. |
Chao-Ning Liu, Ding-Jie Chen, Hwann-Tzong Chen, and Tyng-Luh Liu, "A2A: Attention to Attention Reasoning for Movie Question Answering," 14th Asian Conference on Computer Vision, December 2018, (ACCV) ::: |
40. |
Shou-Yao Tseng, Hwann-Tzong Chen, Shao-Heng Tai, and Tyng-Luh Liu, "Non-local RoI for Cross-Object Perception," NeurIPS 2018 Workshop on Relational Representation Learning, December 2018. ::: |
41. |
Jen-Chun Lin, Wen-Li Wei, Tyng-Luh Liu, Yi-Hsuan Yang, Hsin-Min Wang, Hsiao-Rong Tyan, and Hong-Yuan Mark Liao, "Coherent Deep-Net Fusion To Classify Shots In Concert Videos," IEEE Transactions on Multimedia, volume 20, number 11, pages 3123-3136, November 2018. ::: |
42. |
Hsien-Tzu Cheng, Chun-Hung Chao, Jin-Dong Dong, Hao-Kai Wen, Tyng-Luh Liu, and Min Sun, "Cube Padding for Weakly-Supervised Saliency Prediction in 360° Videos," IEEE Computer Society International Conference on Computer Vision and Pattern Recognition, Salt Lake City, Utah, June 2018, (CVPR) ::: |
43. |
Tyng-Luh Liu, "Guided Co-training for Large-Scale Multi-View Spectral Clustering," arXiv:1707.09866, July 2017. |
44. |
Wen-Li Wei, Jen-Chun Lin, Tyng-Luh Liu, Yi-Hsuan Yang, Hsin-Min Wang, Hsiao-Rong Tyan, and Hong-Yuan Mark Liao, "Deep-Net Fusion to Classify Shots in Concert Videos," IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), March 2017. ::: |
45. |
Tsung-Wei Ke, Che-Wei Lin, Tyng-Luh Liu and Davi Geiger, "Variational Convolutional Networks for Human-Centric Annotations," 13th Asian Conference on Computer Vision, November 2016, (ACCV, oral) |
46. |
Tsung-Wei Ke and Tyng-Luh Liu, "Recursive Reduction Net for Large-Scale High-Dimensional Data," IEEE International Conference on Image Processing, September 2016. |
47. |
Chung-Kuei Lee and Tyng-Luh Liu, "Guided Co-Training for Multi-View Spectral Clustering," IEEE International Conference on Image Processing, September 2016. |
48. |
Tsung-Yu Lin, Tsung-Wei Ke and Tyng-Luh Liu, "Implicit Sparse Code Hashing," arXiv:1512.00130, December 2015. |
49. |
Ching-Hang Chen, Tyng-Luh Liu, Yu-Shuen Wang, Hung-Kuo Chu, Nick C. Tang, Hong-Yuan Mark Liao, "Spatio-Temporal Learning of Basketball Offensive Strategies," 2015 ACM Multimedia Conference, October 2015. |
50. |
Jyh-Jing Hwang and Tyng-Luh Liu, "Pixel-wise Deep Learning for Contour Detection," International Conference on Learning Representations, May 2015, (ICLR) |
51. |
Jyh-Jing Hwang and Tyng-Luh Liu, "Contour Detection Using Cost-Sensitive Convolutional Neural Networks," arXiv:1412.6857, December 2014. |
52. |
Tsung-Yu Lin and Tyng-Luh Liu, "Efficient Binary Codes for Extremely High-dimensional Data," IEEE International Conference on Image Processing, October 2014, (ICIP) |
53. |
Tyng-Luh Liu, Kai-Yueh Chang and Shang-Hong Lai, "Exploring Depth Information for Object Segmentation and Detection," International Conference on Pattern Recognition, August 2014, (ICPR) |
54. |
Chun-Wei Liu and Tyng-Luh Liu, "A Sparse Linear Model for Saliency-Guided Decolorization," IEEE International Conference on Image Processing, Melbourne, Australia, September 2013, (ICIP) |
55. |
Ching-Ting Tu, Kung-Hung Lin and Tyng-Luh Liu, "A Two-dimensional Direct Combined Model for Facial Hallucination," IAPR International Conference on Machine Vision Applications, Kyoto, Japan, May 2013. |
56. |
Kai-Yueh Chang, Tyng-Luh Liu, Hwann-Tzong Chen, and Shang-Hong Lai, "Fusing Generic Objectness and Visual Saliency for Salient Object Detection," International Conference on Computer Vision, Barcelona, Spain, November 2011, (ICCV) ::: |
57. |
Yen-Yu Lin, Tyng-Luh Liu, and Chiou-Shann Fuh, "Multiple Kernel Learning for Dimensionality Reduction," IEEE Transactions on Pattern Analysis and Machine Intelligence, volume 33, number 6, pages 1147-1160, June 2011, (TPAMI) ::: |
58. |
Kai-Yueh Chang, Tyng-Luh Liu, and Shang-Hong Lai, "From Co-saliency to Co-segmentation: An Efficient and Fully Unsupervised Energy Minimization Model," IEEE Computer Society International Conference on Computer Vision and Pattern Recognition, Colorado Springs, CO, USA, June 2011, (CVPR) ::: |
59. |
Horng-Horng Lin, Jen-Hui Chuang, and Tyng-Luh Liu, "Regularized Background Adaptation: A Novel Learning Rate Control Scheme for Gaussian Mixture Modeling," IEEE Transactions on Image Processing, volume 20, number 3, pages 822-836, March 2011, (TIP) |
60. |
Yen-Yu Lin, Tyng-Luh Liu, and Chiou-Shann Fuh, "Clustering Complex Data with Group-Dependent Feature Selection," 11th European Conference on Computer Vision, Springer, Crete, Greece, September 2010, (ECCV) ::: |
61. |
Yu-Wu Chu and Tyng-Luh Liu, "Co-occurrence Random Forests for Object Localization and Classification," 9th Asian Conference on Computer Vision, Xi’an, China, September 2009, (ACCV) |
62. |
Yen-Yu Lin, Jyun-Fan Tsai, and Tyng-Luh Liu, "Efficient Discriminative Local Learning for Object Recognition," International Conference on Computer Vision, Kyoto, Japan, September 2009, (ICCV) ::: |
63. |
Kai-Yueh Chang, Tyng-Luh Liu, and Shang-Hong Lai, "Learning Partially-Observed Hidden Conditional Random Fields for Facial Expression Recognition," Conference computer Vision and Pattern Recognition, Miami, FL, USA, June 2009, (CVPR) ::: |
64. |
Horng-Horng Lin, Tyng-Luh Liu, and Jen-Hui Chuang, "Learning a Scene Background Model via Classification," IEEE Transactions on Signal Processing, volume 57, number 5, pages 1641--1654, May 2009, (TSP) |
65. |
Yen-Yu Lin, Tyng-Luh Liu, and Chiou-Shann Fuh, "Dimensionality Reduction for Data in Multiple Feature Representations," Advances in Neural Information Processing Systems 21, MIT Press, 2009, (NIPS) ::: |
66. |
Tien-Lung Chang, Tyng-Luh Liu, and Jen-Hui Chuang, "Improving Local Learning for Object Categorization by Exploring the Effects of Ranking," Conference computer Vision and Pattern Recognition, Anchorage, AK, USA, June 2008, (CVPR) ::: |
67. |
Hwann-Tzong Chen and Tyng-Luh Liu, "Finding Familiar Objects and Their Depth from a Single Image," IEEE International Conference on Image Processing, San Antonio, Texas, USA, September 2007. |
68. |
Yen-Yu Lin, Tyng-Luh Liu, and Chiou-Shann Fuh, "Local Ensemble Kernel Learning for Object Category Recognition," Conference computer Vision and Pattern Recognition, Minneapolis, MN, USA, June 2007, (CVPR, Oral) ::: |
69. |
Tien-Lung Chang, Tyng-Luh Liu, and Jen-Hui Chuang, "Direct Energy Minimization for Super-Resolution on Nonlinear Manifolds," 9th European Conference on Computer Vision, Lecture Notes in Computer Science, 3954, Springer, pages pp. 281-294, Graz, Austria, May 2006, (ECCV) ::: |
70. |
Hwann-Tzong Chen, Tyng-Luh Liu, and Chiou-Shann Fuh, "Segmenting Highly Articulated Video Objects with Weak-Prior Random Forests," 9th European Conference on Computer Vision, Lecture Notes in Computer Science, 3954, Springer, pages pp. 375-385, Graz, Austria, May 2006, (ECCV) ::: |
71. |
Hwann-Tzong Chen, Tyng-Luh Liu, and Chiou-Shann Fuh, "Tone Reproduction: A Perspective from Luminance-Driven Perceptual Grouping," International Journal of Computer Vision, volume 65, number 1-2, pages 73--96, November 2005, (IJCV) |
72. |
Yen-Yu Lin, Tyng-Luh Liu, and Hwann-Tzong Chen, "Semantic Manifold Learning for Image Retrieval," ACM Multimedia, Singapore, November 2005, (ACM MM, Best Student Papers Session) ::: |
73. |
Hwann-Tzong Chen, Tyng-Luh Liu, and Chiou-Shann Fuh, "Learning Effective Image Metrics from Few Pairwise Examples," International Conference on Computer Vision, volume 2, pages 1371-1378, Beijing, China, October 2005, (ICCV) ::: |
74. |
Yen-Yu Lin and Tyng-Luh Liu, "Robust Face Detection with Multi-Class Boosting," Conference computer Vision and Pattern Recognition, volume 1, pages 679-686, San Diego, CA, USA, June 2005, (CVPR) ::: |
75. |
Hwann-Tzong Chen, Huang-Wei Chang, and Tyng-Luh Liu, "Local Discriminant Embedding and Its Variants," Conference computer Vision and Pattern Recognition, volume 2, pages 846-853, San Diego, CA, USA, June 2005, (CVPR, Oral) ::: |
76. |
Hwann-Tzong Chen, Tyng-Luh Liu, and Tien-Lung Chang, "Tone Reproduction: A Perspective from Luminance-Driven Perceptual Grouping," Conference computer Vision and Pattern Recognition, volume 2, pages 369-376, San Diego, CA, USA, June 2005, (CVPR) ::: |
77. |
Hwann-Tzong Chen, Tyng-Luh Liu, and Chiou-Shann Fuh, "Probabilistic Tracking with Adaptive Feature Selection," International Conference on Pattern Recognition, volume 2, pages 736-739, August 2004, (ICPR). |
78. |
Yen-Yu Lin, Tyng-Luh Liu and Chiou-Shann Fuh, "Fast Object Detection with Occlusions," 8th European Conference on Computer Vision, pages 402-413, Prague, Czech Republic, May 2004, (ECCV) ::: |
79. |
Tyng-Luh Liu and Hwann-Tzong Chen, "Real-Time Tracking Using Trust-Region Methods," IEEE Transactions on Pattern Analysis and Machine Intelligence, volume 26, number 3, pages 397-402, March 2004, (TPAMI) |
80. |
Davi Geiger, Tyng-Luh Liu and Robert V. Kohn, "Representation and Self-Similarity of Shapes," IEEE Transactions on Pattern Analysis and Machine Intelligence, volume 25, number 1, pages 86-99, January 2003, (TPAMI) |
81. |
Hwann-Tzong Chen, Horng-Horng Lin and Tyng-Luh Liu, "Multi-Object Tracking Using Dynamical Graph Matching," IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Kauai, Hawaii, December 2001, (CVPR) ::: |
82. |
Hwann-Tzong Chen and Tyng-Luh Liu, "Trust-Region Methods for Real-Time Tracking," 8th International Conference on Computer Vision, volume 2, pages 717-722, Vancouver, Canada, July 2001, (ICCV) ::: |
83. |
Tyng-Luh Liu and Hwann-Tzong Chen., "A Variational Approach for Digital Watermarking," International Conference on Image Processing, volume 3, pages 674-677, September 2000, (ICIP). |
84. |
Davi Geiger, Tyng-Luh Liu and Michael J. Donahue, "Sparse Representations for Image Decompositions," International Journal of Computer Vision, volume 33, number 2, pages 139-156, September 1999, (IJCV) |
85. |
Tyng-Luh Liu and Davi Geiger, "Approximate Tree Matching and Shape Similarity," 7th International Conference on Computer Vision, pages 456-462, Kerkyra, Greece, September 1999, (ICCV) ::: |
86. |
Tyng-Luh Liu, Davi Geiger and Robert V. Kohn, "Representation and Self-Similarity of Shapes," 6th International Conference on Computer Vision, pages 1129-1135, Bombay, India, January 1998, (ICCV) ::: |
87. |
Tyng-Luh Liu, Mike Donahue, Davi Geiger and Robert Hummel, "Image Recognition with Occlusions," 4th European Conference on Computer Vision, Lecture Notes in Computer Science, 1064, pages 556-565, London, 1996, (ECCV) |
88. |
Mike Donahue, Davi Geiger, Robert Hummel and Tyng-Luh Liu, "Sparse Representations for Image Decomposition with Occlusions," Proc. Computer Vision and Pattern Recognition, pages 7-12, San Francisco, 1996, (CVPR, Oral) |
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