74 citations · 87 across the 9 of their papers we have counts for
9 papers · 1 filter
CostFormer:Cost Transformer for Cost Aggregation in Multi-view Stereo
Weitao Chen, Hongbin Xu, Zhipeng Zhou +4
The core of Multi-view Stereo(MVS) is the matching process among reference and source pixels. Cost aggregation plays a significant role in this process, while previous methods focu…
Semi-supervised Deep Multi-view Stereo
Hongbin Xu, Weitao Chen, Yang Liu +5
Significant progress has been witnessed in learning-based Multi-view Stereo (MVS) under supervised and unsupervised settings. To combine their respective merits in accuracy and com…
From Noise to Feature: Exploiting Intensity Distribution as a Novel Soft Biometric Trait for Finger Vein Recognition
Wenxiong Kang, Yuting Lu, Dejian Li +1
Most finger vein feature extraction algorithms achieve satisfactory performance due to their texture representation abilities, despite simultaneously ignoring the intensity distrib…
Unconstrained Face Sketch Synthesis via Perception-Adaptive Network and A New Benchmark
Lin Nie, Lingbo Liu, Zhengtao Wu +1
Face sketch generation has attracted much attention in the field of visual computing. However, existing methods either are limited to constrained conditions or heavily rely on vari…
Digging into Uncertainty in Self-supervised Multi-view Stereo
Hongbin Xu, Zhipeng Zhou, Yali Wang +4
Self-supervised Multi-view stereo (MVS) with a pretext task of image reconstruction has achieved significant progress recently. However, previous methods are built upon intuitions,…
Self-supervised Multi-view Stereo via Effective Co-Segmentation and Data-Augmentation
Hongbin Xu, Zhipeng Zhou, Yu Qiao +2
Recent studies have witnessed that self-supervised methods based on view synthesis obtain clear progress on multi-view stereo (MVS). However, existing methods rely on the assumptio…
JGR-P2O: Joint Graph Reasoning based Pixel-to-Offset Prediction Network for 3D Hand Pose Estimation from a Single Depth Image
Linpu Fang, Xingyan Liu, Li Liu +2
State-of-the-art single depth image-based 3D hand pose estimation methods are based on dense predictions, including voxel-to-voxel predictions, point-to-point regression, and pixel…
Dynamic Group Convolution for Accelerating Convolutional Neural Networks
Zhuo Su, Linpu Fang, Wenxiong Kang +3
Replacing normal convolutions with group convolutions can significantly increase the computational efficiency of modern deep convolutional networks, which has been widely adopted i…
Universal-RCNN: Universal Object Detector via Transferable Graph R-CNN
Hang Xu, Linpu Fang, Xiaodan Liang +2
The dominant object detection approaches treat each dataset separately and fit towards a specific domain, which cannot adapt to other domains without extensive retraining. In this…