activity
20202026
most citedLearning to Purification for Unsupervised Person Re-identification

99 citations · 135 across the 12 of their papers we have counts for

collaborators

12 papers

cs.CV2026

FreeSpec: Training-Free Long Video Generation via Singular-Spectrum Reconstruction

Fangda Chen, Shanshan Zhao, Longrong Yang +3

Video diffusion models perform well in short-video synthesis, but their training-free extension to long videos often suffers from content drift, temporal inconsistency, and over-sm…

cs.CV2024

Temporal-Enhanced Multimodal Transformer for Referring Multi-Object Tracking and Segmentation

Changcheng Xiao, Qiong Cao, Yujie Zhong +4

Referring multi-object tracking (RMOT) is an emerging cross-modal task that aims to locate an arbitrary number of target objects and maintain their identities referred by a languag…

cs.CV2024★ 1 cited

MambaTrack: A Simple Baseline for Multiple Object Tracking with State Space Model

Changcheng Xiao, Qiong Cao, Zhigang Luo +1

Tracking by detection has been the prevailing paradigm in the field of Multi-object Tracking (MOT). These methods typically rely on the Kalman Filter to estimate the future locatio…

cs.LG2023★ 9 cited

CoCo: A Coupled Contrastive Framework for Unsupervised Domain Adaptive Graph Classification

Nan Yin, Li Shen, Mengzhu Wang +5

Although graph neural networks (GNNs) have achieved impressive achievements in graph classification, they often need abundant task-specific labels, which could be extensively costl…

cs.CV2023★ 1 cited

MotionTrack: Learning Motion Predictor for Multiple Object Tracking

Changcheng Xiao, Qiong Cao, Yujie Zhong +4

Significant progress has been achieved in multi-object tracking (MOT) through the evolution of detection and re-identification (ReID) techniques. Despite these advancements, accura…

cs.CV2023

MagicFusion: Boosting Text-to-Image Generation Performance by Fusing Diffusion Models

Jing Zhao, Heliang Zheng, Chaoyue Wang +2

The advent of open-source AI communities has produced a cornucopia of powerful text-guided diffusion models that are trained on various datasets. While few explorations have been c…