65 citations · 153 across the 7 of their papers we have counts for
8 papers
Primitive3D: 3D Object Dataset Synthesis from Randomly Assembled Primitives
Xinke Li, Henghui Ding, Zekun Tong +2
Numerous advancements in deep learning can be attributed to the access to large-scale and well-annotated datasets. However, such a dataset is prohibitively expensive in 3D computer…
Bridging the Source-to-target Gap for Cross-domain Person Re-Identification with Intermediate Domains
Yongxing Dai, Yifan Sun, Jun Liu +3
Cross-domain person re-identification (re-ID), such as unsupervised domain adaptive (UDA) re-ID, aims to transfer the identity-discriminative knowledge from the source to the targe…
IDM: An Intermediate Domain Module for Domain Adaptive Person Re-ID
Yongxing Dai, Jun Liu, Yifan Sun +3
Unsupervised domain adaptive person re-identification (UDA re-ID) aims at transferring the labeled source domain's knowledge to improve the model's discriminability on the unlabele…
Generalizable Person Re-identification with Relevance-aware Mixture of Experts
Yongxing Dai, Xiaotong Li, Jun Liu +2
Domain generalizable (DG) person re-identification (ReID) is a challenging problem because we cannot access any unseen target domain data during training. Almost all the existing D…
Dual-Refinement: Joint Label and Feature Refinement for Unsupervised Domain Adaptive Person Re-Identification
Yongxing Dai, Jun Liu, Yan Bai +2
Unsupervised domain adaptive (UDA) person re-identification (re-ID) is a challenging task due to the missing of labels for the target domain data. To handle this problem, some rece…
Campus3D: A Photogrammetry Point Cloud Benchmark for Hierarchical Understanding of Outdoor Scene
Xinke Li, Chongshou Li, Zekun Tong +5
Learning on 3D scene-based point cloud has received extensive attention as its promising application in many fields, and well-annotated and multisource datasets can catalyze the de…