317 citations · 1.3k across the 37 of their papers we have counts for
14 papers · 1 filter
Playing for 3D Human Recovery
Zhongang Cai, Mingyuan Zhang, Jiawei Ren +7
Image- and video-based 3D human recovery (i.e., pose and shape estimation) have achieved substantial progress. However, due to the prohibitive cost of motion capture, existing data…
Encoder-decoder with Multi-level Attention for 3D Human Shape and Pose Estimation
Ziniu Wan, Zhengjia Li, Maoqing Tian +3
3D human shape and pose estimation is the essential task for human motion analysis, which is widely used in many 3D applications. However, existing methods cannot simultaneously ca…
GroupFormer: Group Activity Recognition with Clustered Spatial-Temporal Transformer
Shuaicheng Li, Qianggang Cao, Lingbo Liu +4
Group activity recognition is a crucial yet challenging problem, whose core lies in fully exploring spatial-temporal interactions among individuals and generating reasonable group…
CSG-Stump: A Learning Friendly CSG-Like Representation for Interpretable Shape Parsing
Daxuan Ren, Jianmin Zheng, Jianfei Cai +8
Generating an interpretable and compact representation of 3D shapes from point clouds is an important and challenging problem. This paper presents CSG-Stump Net, an unsupervised en…
Unsupervised Domain Adaptive 3D Detection with Multi-Level Consistency
Zhipeng Luo, Zhongang Cai, Changqing Zhou +7
Deep learning-based 3D object detection has achieved unprecedented success with the advent of large-scale autonomous driving datasets. However, drastic performance degradation rema…
Collaborative Unsupervised Visual Representation Learning from Decentralized Data
Weiming Zhuang, Xin Gan, Yonggang Wen +2
Unsupervised representation learning has achieved outstanding performances using centralized data available on the Internet. However, the increasing awareness of privacy protection…
Learning Geometry-Guided Depth via Projective Modeling for Monocular 3D Object Detection
Yinmin Zhang, Xinzhu Ma, Shuai Yi +4
As a crucial task of autonomous driving, 3D object detection has made great progress in recent years. However, monocular 3D object detection remains a challenging problem due to th…
Domain Consistency Regularization for Unsupervised Multi-source Domain Adaptive Classification
Zhipeng Luo, Xiaobing Zhang, Shijian Lu +1
Deep learning-based multi-source unsupervised domain adaptation (MUDA) has been actively studied in recent years. Compared with single-source unsupervised domain adaptation (SUDA),…
Delving Deep into the Generalization of Vision Transformers under Distribution Shifts
Chongzhi Zhang, Mingyuan Zhang, Shanghang Zhang +6
Vision Transformers (ViTs) have achieved impressive performance on various vision tasks, yet their generalization under distribution shifts (DS) is rarely understood. In this work,…
Towards Unsupervised Domain Adaptation for Deep Face Recognition under Privacy Constraints via Federated Learning
Weiming Zhuang, Xin Gan, Yonggang Wen +3
Unsupervised domain adaptation has been widely adopted to generalize models for unlabeled data in a target domain, given labeled data in a source domain, whose data distributions d…
Unsupervised 3D Shape Completion through GAN Inversion
Junzhe Zhang, Xinyi Chen, Zhongang Cai +6
Most 3D shape completion approaches rely heavily on partial-complete shape pairs and learn in a fully supervised manner. Despite their impressive performances on in-domain data, wh…
Variational Relational Point Completion Network
Liang Pan, Xinyi Chen, Zhongang Cai +4
Real-scanned point clouds are often incomplete due to viewpoint, occlusion, and noise. Existing point cloud completion methods tend to generate global shape skeletons and hence lac…
Delving into Localization Errors for Monocular 3D Object Detection
Xinzhu Ma, Yinmin Zhang, Dan Xu +4
Estimating 3D bounding boxes from monocular images is an essential component in autonomous driving, while accurate 3D object detection from this kind of data is very challenging. I…
HAVANA: Hierarchical and Variation-Normalized Autoencoder for Person Re-identification
Jiawei Ren, Xiao Ma, Chen Xu +2
Person Re-Identification (Re-ID) is of great importance to the many video surveillance systems. Learning discriminative features for Re-ID remains a challenge due to the large vari…