1 code implementation • CVPR 2022 • Mingbo Hong, Yuhang Lu, Nianjin Ye, Chunyu Lin, Qijun Zhao, Shuaicheng Liu
Estimating homography from an image pair is a fundamental problem in image alignment.
2 code implementations • 7 Jun 2021 • Hao Xu, Nianjin Ye, Guanghui Liu, Bing Zeng, Shuaicheng Liu
Data association is important in the point cloud registration.
1 code implementation • ICCV 2021 • Nianjin Ye, Chuan Wang, Haoqiang Fan, Shuaicheng Liu
Last, we propose a Feature Identity Loss (FIL) to enforce the learned image feature warp-equivariant, meaning that the result should be identical if the order of warp operation and feature extraction is swapped.
no code implementations • 30 Jun 2020 • Kunming Luo, Chuan Wang, Nianjin Ye, Shuaicheng Liu, Jue Wang
Occlusion is an inevitable and critical problem in unsupervised optical flow learning.
no code implementations • 11 Dec 2019 • Nianjin Ye, Chuan Wang, Shuaicheng Liu, Lanpeng Jia, Jue Wang, Yongqing Cui
Deep homography methods, on the other hand, are free from such problem by learning deep features for robust performance.
1 code implementation • ECCV 2020 • Jirong Zhang, Chuan Wang, Shuaicheng Liu, Lanpeng Jia, Nianjin Ye, Jue Wang, Ji Zhou, Jian Sun
Homography estimation is a basic image alignment method in many applications.
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