activity
20212025
most citedExploring Fine-Grained Representation and Recomposition for Cloth-Changing Person Re-Identification

45 citations · 62 across the 12 of their papers we have counts for

collaborators

12 papers

cs.CV2025

Uni3C: Unifying Precisely 3D-Enhanced Camera and Human Motion Controls for Video Generation

Chenjie Cao, Jingkai Zhou, Shikai Li +5

Camera and human motion controls have been extensively studied for video generation, but existing approaches typically address them separately, suffering from limited data with hig…

cs.CV2025

DecoFuse: Decomposing and Fusing the "What", "Where", and "How" for Brain-Inspired fMRI-to-Video Decoding

Chong Li, Jingyang Huo, Weikang Gong +3

Decoding visual experiences from brain activity is a significant challenge. Existing fMRI-to-video methods often focus on semantic content while overlooking spatial and motion info…

cs.CV2024

MVGenMaster: Scaling Multi-View Generation from Any Image via 3D Priors Enhanced Diffusion Model

Chenjie Cao, Chaohui Yu, Shang Liu +3

We introduce MVGenMaster, a multi-view diffusion model enhanced with 3D priors to address versatile Novel View Synthesis (NVS) tasks. MVGenMaster leverages 3D priors that are warpe…

cs.CV2024

Improving Neural Surface Reconstruction with Feature Priors from Multi-View Image

Xinlin Ren, Chenjie Cao, Yanwei Fu +1

Recent advancements in Neural Surface Reconstruction (NSR) have significantly improved multi-view reconstruction when coupled with volume rendering. However, relying solely on phot…

cs.RO2024★ 1 cited

LAC-Net: Linear-Fusion Attention-Guided Convolutional Network for Accurate Robotic Grasping Under the Occlusion

Jinyu Zhang, Yongchong Gu, Jianxiong Gao +5

This paper addresses the challenge of perceiving complete object shapes through visual perception. While prior studies have demonstrated encouraging outcomes in segmenting the visi…

cs.CV2024

Hyper-Transformer for Amodal Completion

Jianxiong Gao, Xuelin Qian, Longfei Liang +2

Amodal object completion is a complex task that involves predicting the invisible parts of an object based on visible segments and background information. Learning shape priors is…

cs.CV2024★ 5 cited

Image-Text-Image Knowledge Transfer for Lifelong Person Re-Identification with Hybrid Clothing States

Qizao Wang, Xuelin Qian, Bin Li +2

With the continuous expansion of intelligent surveillance networks, lifelong person re-identification (LReID) has received widespread attention, pursuing the need of self-evolution…

cs.CV2024★ 9 cited

Content and Salient Semantics Collaboration for Cloth-Changing Person Re-Identification

Qizao Wang, Xuelin Qian, Bin Li +3

Cloth-changing person re-identification aims at recognizing the same person with clothing changes across non-overlapping cameras. Advanced methods either resort to identity-related…

cs.CV2024

Pushing Auto-regressive Models for 3D Shape Generation at Capacity and Scalability

Xuelin Qian, Yu Wang, Simian Luo +9

Auto-regressive models have achieved impressive results in 2D image generation by modeling joint distributions in grid space. In this paper, we extend auto-regressive models to 3D…

cs.CV2023

fMRI-PTE: A Large-scale fMRI Pretrained Transformer Encoder for Multi-Subject Brain Activity Decoding

Xuelin Qian, Yun Wang, Jingyang Huo +2

The exploration of brain activity and its decoding from fMRI data has been a longstanding pursuit, driven by its potential applications in brain-computer interfaces, medical diagno…

cs.CV2023★ 45 cited

Exploring Fine-Grained Representation and Recomposition for Cloth-Changing Person Re-Identification

Qizao Wang, Xuelin Qian, Bin Li +2

Cloth-changing person Re-IDentification (Re-ID) is a particularly challenging task, suffering from two limitations of inferior discriminative features and limited training samples.…

eess.IV2021★ 2 cited

Rapid COVID-19 Risk Screening by Eye-region Manifestations

Yanwei Fu, Lei Zhao, Haojie Zheng +13

It is still nontrivial to develop a new fast COVID-19 screening method with the easier access and lower cost, due to the technical and cost limitations of the current testing metho…