| Multiple Hypothesis Tracking Revisited C Kim, F Li, A Ciptadi, JM Rehg Proceedings of the IEEE International Conference on Computer Vision, 4696-4704, 2015 | 471 | 2015 |
| Video Segmentation by Tracking Many Figure-Ground Segments F Li, T Kim, A Humayun, D Tsai, JM Rehg Computer Vision (ICCV), 2013 IEEE International Conference on, 2192-2199, 2013 | 438 | 2013 |
| Pointconv: Deep convolutional networks on 3d point clouds W Wu, Z Qi, L Fuxin Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 287 | 2019 |
| Joint semantic segmentation and 3d reconstruction from monocular video A Kundu, Y Li, F Dellaert, F Li, JM Rehg European Conference on Computer Vision, 703-718, 2014 | 238 | 2014 |
| Adversarial examples detection in deep networks with convolutional filter statistics X Li, F Li Proceedings of the IEEE International Conference on Computer Vision, 5764-5772, 2017 | 228 | 2017 |
| Latent structured models for human pose estimation C Ionescu, F Li, C Sminchisescu 2011 International Conference on Computer Vision, 2220-2227, 2011 | 180 | 2011 |
| Object recognition as ranking holistic figure-ground hypotheses F Li, J Carreira, C Sminchisescu Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on …, 2010 | 162 | 2010 |
| Human urine proteome analysis by three separation approaches W Sun, F Li, S Wu, X Wang, D Zheng, J Wang, Y Gao Proteomics 5 (18), 4994-5001, 2005 | 158 | 2005 |
| Object recognition by sequential figure-ground ranking J Carreira, F Li, C Sminchisescu International journal of computer vision 98 (3), 243-262, 2012 | 153 | 2012 |
| Concanavalin A-captured glycoproteins in healthy human urine L Wang, F Li, W Sun, S Wu, X Wang, L Zhang, D Zheng, J Wang, Y Gao Molecular & Cellular Proteomics 5 (3), 560-562, 2006 | 142 | 2006 |
| RIGOR: Reusing Inference in Graph Cuts for generating Object Regions A Humayun, F Li, JM Rehg Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on, 336-343, 2014 | 138 | 2014 |
| Multi-object Tracking with Neural Gating Using Bilinear LSTM C Kim, F Li, J Rehg Proceedings of the European Conference on Computer Vision (ECCV), 200-215, 2018 | 134 | 2018 |
| Learning multiple-question decision trees for cold-start recommendation M Sun, F Li, J Lee, K Zhou, G Lebanon, H Zha Proceedings of the sixth ACM international conference on Web search and data …, 2013 | 93 | 2013 |
| Random Fourier approximations for skewed multiplicative histogram kernels F Li, C Ionescu, C Sminchisescu Joint Pattern Recognition Symposium, 262-271, 2010 | 89 | 2010 |
| Open Set Learning with Counterfactual Images L Neal, M Olson, X Fern, WK Wong, F Li Proceedings of the European Conference on Computer Vision (ECCV), 613-628, 2018 | 75 | 2018 |
| Efficient learning of continuous-time hidden markov models for disease progression YY Liu, S Li, F Li, L Song, JM Rehg Advances in neural information processing systems 28, 3600-3608, 2015 | 65 | 2015 |
| Convex multiple-instance learning by estimating likelihood ratio F Li, C Sminchisescu Advances in Neural Information Processing Systems, 1360-1368, 2010 | 54 | 2010 |
| Fourier kernel learning EG Băzăvan, F Li, C Sminchisescu European Conference on Computer Vision, 459-473, 2012 | 52 | 2012 |
| AMASS: software for automatically validating the quality of MS/MS spectrum from SEQUEST results W Sun, F Li, J Wang, D Zheng, Y Gao Molecular & Cellular Proteomics 3 (12), 1194-1199, 2004 | 48 | 2004 |
| Adaptive wing loss for robust face alignment via heatmap regression X Wang, L Bo, L Fuxin Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 43 | 2019 |
James M. RehgProfessor of Computer Science, Georgia Institute of TechnologyVerified email at gatech.edu
