| Location recognition using prioritized feature matching Y Li, N Snavely, DP Huttenlocher Computer Vision–ECCV 2010: 11th European Conference on Computer Vision …, 2010 | 549 | 2010 |
| Worldwide pose estimation using 3d point clouds Y Li, N Snavely, D Huttenlocher, P Fua European conference on computer vision, 15-29, 2012 | 488 | 2012 |
| Landmark classification in large-scale image collections Y Li, DJ Crandall, DP Huttenlocher 2009 IEEE 12th international conference on computer vision, 1957-1964, 2009 | 372 | 2009 |
| CIDRE: an illumination-correction method for optical microscopy K Smith, Y Li, F Piccinini, G Csucs, C Balazs, A Bevilacqua, P Horvath Nature methods 12 (5), 404-406, 2015 | 144 | 2015 |
| Learning for structured prediction using approximate subgradient descent with working sets A Lucchi, Y Li, P Fua Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2013 | 110 | 2013 |
| Structured image segmentation using kernelized features A Lucchi, Y Li, K Smith, P Fua Computer Vision–ECCV 2012: 12th European Conference on Computer Vision …, 2012 | 91 | 2012 |
| Are spatial and global constraints really necessary for segmentation? A Lucchi, Y Li, X Boix, K Smith, P Fua 2011 international conference on computer vision, 9-16, 2011 | 87 | 2011 |
| Generating sharp panoramas from motion-blurred videos Y Li, SB Kang, N Joshi, SM Seitz, DP Huttenlocher 2010 IEEE Computer Society Conference on Computer Vision and Pattern …, 2010 | 84 | 2010 |
| Learning for stereo vision using the structured support vector machine Y Li, DP Huttenlocher 2008 IEEE Conference on Computer Vision and Pattern Recognition, 1-8, 2008 | 68 | 2008 |
| Generating sharp images, panoramas, and videos from motion-blurred videos Y Li, SB Kang, NS Joshi, SM Seitz US Patent 8,428,390, 2013 | 55 | 2013 |
| Learning for optical flow using stochastic optimization Y Li, DP Huttenlocher Computer Vision–ECCV 2008: 10th European Conference on Computer Vision …, 2008 | 55 | 2008 |
| Sparse long-range random field and its application to image denoising Y Li, DP Huttenlocher Computer Vision–ECCV 2008: 10th European Conference on Computer Vision …, 2008 | 48 | 2008 |
| Learning structured models for segmentation of 2-D and 3-D imagery A Lucchi, P Márquez-Neila, C Becker, Y Li, K Smith, G Knott, P Fua IEEE transactions on medical imaging 34 (5), 1096-1110, 2014 | 47 | 2014 |
| SEANet: A multi-modal speech enhancement network M Tagliasacchi, Y Li, K Misiunas, D Roblek arXiv preprint arXiv:2009.02095, 2020 | 38 | 2020 |
| Real-time speech frequency bandwidth extension Y Li, M Tagliasacchi, O Rybakov, V Ungureanu, D Roblek ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 35 | 2021 |
| Robot navigation using 1d panoramic images A Briggs, Y Li, D Scharstein, M Wilder Proceedings 2006 IEEE International Conference on Robotics and Automation …, 2006 | 33 | 2006 |
| From here to there: Video inbetweening using direct 3d convolutions Y Li, D Roblek, M Tagliasacchi arXiv preprint arXiv:1905.10240, 2019 | 22 | 2019 |
| Matching scale-space features in 1D panoramas AJ Briggs, C Detweiler, Y Li, PC Mullen, D Scharstein Computer vision and image understanding 103 (3), 184-195, 2006 | 22 | 2006 |
| Learning to denoise historical music Y Li, B Gfeller, M Tagliasacchi, D Roblek arXiv preprint arXiv:2008.02027, 2020 | 16 | 2020 |
| Feature matching across 1d panoramas A Briggs, Y Li, D Scharstein 6thWorkshop on Omnidirectional Vision, 2005 | 8 | 2005 |
Daniel HuttenlocherMassachusetts Institute of TechnologyVerified email at mit.edu
