24 citations · 75 across the 9 of their papers we have counts for
11 papers
Transformer Based Multi-Grained Features for Unsupervised Person Re-Identification
Jiachen Li, Menglin Wang, Xiaojin Gong
Multi-grained features extracted from convolutional neural networks (CNNs) have demonstrated their strong discrimination ability in supervised person re-identification (Re-ID) task…
Online Convolutional Re-parameterization
Mu Hu, Junyi Feng, Jiashen Hua +4
Structural re-parameterization has drawn increasing attention in various computer vision tasks. It aims at improving the performance of deep models without introducing any inferenc…
PENet: Towards Precise and Efficient Image Guided Depth Completion
Mu Hu, Shuling Wang, Bin Li +3
Image guided depth completion is the task of generating a dense depth map from a sparse depth map and a high quality image. In this task, how to fuse the color and depth modalities…
Self-supervised Visual-LiDAR Odometry with Flip Consistency
Bin Li, Mu Hu, Shuling Wang +2
Most learning-based methods estimate ego-motion by utilizing visual sensors, which suffer from dramatic lighting variations and textureless scenarios. In this paper, we incorporate…
Camera-aware Proxies for Unsupervised Person Re-Identification
Menglin Wang, Baisheng Lai, Jianqiang Huang +2
This paper tackles the purely unsupervised person re-identification (Re-ID) problem that requires no annotations. Some previous methods adopt clustering techniques to generate pseu…
Towards Precise Intra-camera Supervised Person Re-identification
Menglin Wang, Baisheng Lai, Haokun Chen +3
Intra-camera supervision (ICS) for person re-identification (Re-ID) assumes that identity labels are independently annotated within each camera view and no inter-camera identity as…