201 citations · 540 across the 24 of their papers we have counts for
6 papers · 1 filter
BlendedMVS: A Large-scale Dataset for Generalized Multi-view Stereo Networks
Yao Yao, Zixin Luo, Shiwei Li +5
While deep learning has recently achieved great success on multi-view stereo (MVS), limited training data makes the trained model hard to be generalized to unseen scenarios. Compar…
Self-Supervised Learning of Depth and Motion Under Photometric Inconsistency
Tianwei Shen, Lei Zhou, Zixin Luo +5
The self-supervised learning of depth and pose from monocular sequences provides an attractive solution by using the photometric consistency of nearby frames as it depends much les…
Learning Two-View Correspondences and Geometry Using Order-Aware Network
Jiahui Zhang, Dawei Sun, Zixin Luo +6
Establishing correspondences between two images requires both local and global spatial context. Given putative correspondences of feature points in two views, in this paper, we pro…
ContextDesc: Local Descriptor Augmentation with Cross-Modality Context
Zixin Luo, Tianwei Shen, Lei Zhou +5
Most existing studies on learning local features focus on the patch-based descriptions of individual keypoints, whereas neglecting the spatial relations established from their keyp…
Recurrent MVSNet for High-resolution Multi-view Stereo Depth Inference
Yao Yao, Zixin Luo, Shiwei Li +3
Deep learning has recently demonstrated its excellent performance for multi-view stereo (MVS). However, one major limitation of current learned MVS approaches is the scalability: t…
Beyond Photometric Loss for Self-Supervised Ego-Motion Estimation
Tianwei Shen, Zixin Luo, Lei Zhou +4
Accurate relative pose is one of the key components in visual odometry (VO) and simultaneous localization and mapping (SLAM). Recently, the self-supervised learning framework that…