| Learning memory-guided normality for anomaly detection H Park, J Noh, B Ham Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 352 | 2020 |
| Fast global image smoothing based on weighted least squares D Min, S Choi, J Lu, B Ham, K Sohn, MN Do IEEE Transactions on Image Processing 23 (12), 5638-5653, 2014 | 344 | 2014 |
| Robust guided image filtering using nonconvex potentials B Ham, M Cho, J Ponce IEEE transactions on pattern analysis and machine intelligence 40 (1), 192-207, 2017 | 142 | 2017 |
| Proposal flow B Ham, M Cho, C Schmid, J Ponce Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016 | 140 | 2016 |
| Fcss: Fully convolutional self-similarity for dense semantic correspondence S Kim, D Min, B Ham, S Jeon, S Lin, K Sohn Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 138 | 2017 |
| Robust image filtering using joint static and dynamic guidance B Ham, M Cho, J Ponce Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 137 | 2015 |
| Scnet: Learning semantic correspondence K Han, RS Rezende, B Ham, KYK Wong, M Cho, C Schmid, J Ponce Proceedings of the IEEE international conference on computer vision, 1831-1840, 2017 | 125 | 2017 |
| DASC: Dense adaptive self-correlation descriptor for multi-modal and multi-spectral correspondence S Kim, D Min, B Ham, S Ryu, MN Do, K Sohn Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 96 | 2015 |
| Sfnet: Learning object-aware semantic correspondence J Lee, D Kim, J Ponce, B Ham Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 93 | 2019 |
| Proposal flow: Semantic correspondences from object proposals B Ham, M Cho, C Schmid, J Ponce IEEE transactions on pattern analysis and machine intelligence 40 (7), 1711-1725, 2017 | 90 | 2017 |
| Relation network for person re-identification H Park, B Ham Proceedings of the AAAI conference on artificial intelligence 34 (07), 11839 …, 2020 | 79 | 2020 |
| Learning with privileged information for efficient image super-resolution W Lee, J Lee, D Kim, B Ham Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 72 | 2020 |
| Visual fatigue evaluation and enhancement for 2D-plus-depth video J Choi, D Kim, B Ham, S Choi, K Sohn 2010 IEEE International Conference on Image Processing, 2981-2984, 2010 | 70 | 2010 |
| Learning disentangled representation for robust person re-identification C Eom, B Ham Advances in neural information processing systems 32, 2019 | 58 | 2019 |
| Depth analogy: Data-driven approach for single image depth estimation using gradient samples S Choi, D Min, B Ham, Y Kim, C Oh, K Sohn IEEE Transactions on Image Processing 24 (12), 5953-5966, 2015 | 54 | 2015 |
| Deformable kernel networks for joint image filtering B Kim, J Ponce, B Ham International Journal of Computer Vision 129 (2), 579-600, 2021 | 51 | 2021 |
| Space-time hole filling with random walks in view extrapolation for 3D video S Choi, B Ham, K Sohn IEEE Transactions on Image Processing 22 (6), 2429-2441, 2013 | 51 | 2013 |
| Network quantization with element-wise gradient scaling J Lee, D Kim, B Ham Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 41 | 2021 |
| Hvpr: Hybrid voxel-point representation for single-stage 3d object detection J Noh, S Lee, B Ham Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 41 | 2021 |
| Mahalanobis distance cross-correlation for illumination-invariant stereo matching S Kim, B Ham, B Kim, K Sohn IEEE Transactions on Circuits and Systems for Video Technology 24 (11), 1844 …, 2014 | 41 | 2014 |
Kwanghoon SohnYonsei UniversityПотвърден имейл адрес: yonsei.ac.kr
