MDA-Net: Memorable Domain Adaptation Network for Monocular Depth Estimation J Zhu, Y Shi, M Ren, Y Fang British Machine Vision Conference, 2020 | 11* | 2020 |
Self-supervised learning of depth and ego-motion with differentiable bundle adjustment Y Shi, J Zhu, Y Fang, K Lien, J Gu arXiv preprint arXiv:1909.13163, 2019 | 11 | 2019 |
EGA-Depth: Efficient Guided Attention for Self-Supervised Multi-Camera Depth Estimation Y Shi, H Cai, A Ansari, F Porikli Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 8 | 2023 |
Pairwise Attention Encoding for Point Cloud Feature Learning Y Shi, H Fang, J Zhu, Y Fang International Conference on 3D Vision, 135-144, 2019 | 4 | 2019 |
MAMo: Leveraging Memory and Attention for Monocular Video Depth Estimation R Yasarla, H Cai, J Jeong, Y Shi, R Garrepalli, F Porikli Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023 | 3 | 2023 |
FutureDepth: Learning to Predict the Future Improves Video Depth Estimation R Yasarla, MK Singh, H Cai, Y Shi, J Jeong, Y Zhu, S Han, R Garrepalli, ... arXiv preprint arXiv:2403.12953, 2024 | 1 | 2024 |
DeCoTR: Enhancing Depth Completion with 2D and 3D Attentions Y Shi, MK Singh, H Cai, F Porikli Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | | 2024 |
Adaptive Regularization: Oracle Property and Applications Y Shi, X He, H Wu, ZX Jin, W Lu International Conference on Neural Information Processing, 13-23, 2017 | | 2017 |
Supplementary for MAMo: Leveraging Memory and Attention for Monocular Video Depth Estimation R Yasarla, H Cai, J Jeong, Y Shi, R Garrepalli, F Porikli | | |