Ava: A video dataset of spatio-temporally localized atomic visual actions C Gu, C Sun, DA Ross, C Vondrick, C Pantofaru, Y Li, ... Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 1232 | 2018 |
Sfm-net: Learning of structure and motion from video S Vijayanarasimhan, S Ricco, C Schmid, R Sukthankar, K Fragkiadaki arXiv preprint arXiv:1704.07804, 2017 | 524 | 2017 |
Correcting motion artifacts in retinal spectral domain optical coherence tomography via image registration S Ricco, M Chen, H Ishikawa, G Wollstein, J Schuman Medical Image Computing and Computer-Assisted Intervention–MICCAI 2009: 12th …, 2009 | 117 | 2009 |
Selecting and presenting representative frames for video previews S Shetty, T Izo, MH Tsai, S Vijayanarasimhan, A Natsev, S Abu-El-Haija, ... US Patent 9,953,222, 2018 | 70 | 2018 |
A step toward more inclusive people annotations for fairness C Schumann, S Ricco, U Prabhu, V Ferrari, C Pantofaru Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society, 916-925, 2021 | 64 | 2021 |
Articulated motion discovery using pairs of trajectories L Del Pero, S Ricco, R Sukthankar, V Ferrari Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 50 | 2015 |
Dense lagrangian motion estimation with occlusions S Ricco, C Tomasi 2012 IEEE Conference on Computer Vision and Pattern Recognition, 1800-1807, 2012 | 48 | 2012 |
Fingerspelling recognition through classification of letter-to-letter transitions S Ricco, C Tomasi Asian conference on computer vision, 214-225, 2009 | 39 | 2009 |
Sfm-net: Learning of structure and motion from video. arXiv 2017 S Vijayanarasimhan, S Ricco, C Schmid, R Sukthankar, K Fragkiadaki arXiv preprint arXiv:1704.07804, 0 | 26 | |
Motion prediction under multimodality with conditional stochastic networks K Fragkiadaki, J Huang, A Alemi, S Vijayanarasimhan, S Ricco, ... arXiv preprint arXiv:1705.02082, 2017 | 24 | 2017 |
Textured occupancy grids for monocular localization without features J Mason, S Ricco, R Parr 2011 IEEE International Conference on Robotics and Automation, 5800-5806, 2011 | 24 | 2011 |
Which skin tone measures are the most inclusive? An investigation of skin tone measures for artificial intelligence CM Heldreth, EP Monk, AT Clark, C Schumann, X Eyee, S Ricco ACM Journal on Responsible Computing 1 (1), 1-21, 2024 | 21 | 2024 |
Behavior discovery and alignment of articulated object classes from unstructured video L Del Pero, S Ricco, R Sukthankar, V Ferrari International Journal of Computer Vision 121, 303-325, 2017 | 21 | 2017 |
Determining structure and motion in images using neural networks CL Schmid, S Vijayanarasimhan, SM Ricco, BA Seybold, R Sukthankar, ... US Patent 10,878,583, 2020 | 19 | 2020 |
Introducing the model card toolkit for easier model transparency reporting H Fang, H Miao, K Shukla, D Nanas, C Xu, C Greer, N Polyzotis, T Doshi, ... Google AI Blog, 2020 | 18 | 2020 |
Video motion for every visible point S Ricco, C Tomasi Proceedings of the IEEE International Conference on Computer Vision, 2464-2471, 2013 | 18 | 2013 |
Consensus and subjectivity of skin tone annotation for ml fairness C Schumann, F Olanubi, A Wright, E Monk, C Heldreth, S Ricco Advances in Neural Information Processing Systems 36, 2024 | 17 | 2024 |
Discovering the physical parts of an articulated object class from multiple videos L Del Pero, S Ricco, R Sukthankar, V Ferrari Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016 | 14 | 2016 |
Imagen 3 J Baldridge, J Bauer, M Bhutani, N Brichtova, A Bunner, K Chan, Y Chen, ... arXiv preprint arXiv:2408.07009, 2024 | 9 | 2024 |
Self-supervised learning of structure and motion from video A Fragkiadaki, B Seybold, C Schmid, R Sukthankar, S Vijayanarasimhan, ... arXiv e-prints, 2017 | 7 | 2017 |