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20172025
most citedExploring Fine-Grained Representation and Recomposition for Cloth-Changing Person Re-Identification

45 citations · 196 across the 27 of their papers we have counts for

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26 papers · 1 filter

cs.CV2025

ChatReID: Open-ended Interactive Person Retrieval via Hierarchical Progressive Tuning for Vision Language Models

Ke Niu, Haiyang Yu, Mengyang Zhao +6

Person re-identification (Re-ID) is a crucial task in computer vision, aiming to recognize individuals across non-overlapping camera views. While recent advanced vision-language mo…

cs.CV2024

MinD-3D++: Advancing fMRI-Based 3D Reconstruction with High-Quality Textured Mesh Generation and a Comprehensive Dataset

Jianxiong Gao, Yanwei Fu, Yuqian Fu +3

Reconstructing 3D visuals from functional Magnetic Resonance Imaging (fMRI) data, introduced as Recon3DMind, is of significant interest to both cognitive neuroscience and computer…

cs.CV2024★ 1 cited

Synthesizing Efficient Data with Diffusion Models for Person Re-Identification Pre-Training

Ke Niu, Haiyang Yu, Xuelin Qian +3

Existing person re-identification (Re-ID) methods principally deploy the ImageNet-1K dataset for model initialization, which inevitably results in sub-optimal situations due to the…

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★ 3 cited

AdalReID: Auto-selected Knowledge Adapters for Lifelong Person Re-identification

Xuelin Qian, Ruiqi Wu, Gong Cheng +3

Lifelong Person Re-Identification (LReID) extends traditional ReID by requiring systems to continually learn from non-overlapping datasets across different times and locations, ada…

cs.CV2024★ 6 cited

Distribution Aligned Semantics Adaption for Lifelong Person Re-Identification

Qizao Wang, Xuelin Qian, Bin Li +1

In real-world scenarios, person Re-IDentification (Re-ID) systems need to be adaptable to changes in space and time. Therefore, the adaptation of Re-ID models to new domains while…

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

NeuroPictor: Refining fMRI-to-Image Reconstruction via Multi-individual Pretraining and Multi-level Modulation

Jingyang Huo, Yikai Wang, Xuelin Qian +4

Recent fMRI-to-image approaches mainly focused on associating fMRI signals with specific conditions of pre-trained diffusion models. These approaches, while producing high-quality…

cs.CV2023★ 1 cited

MinD-3D: Reconstruct High-quality 3D objects in Human Brain

Jianxiong Gao, Yuqian Fu, Yun Wang +3

In this paper, we introduce Recon3DMind, an innovative task aimed at reconstructing 3D visuals from Functional Magnetic Resonance Imaging (fMRI) signals, marking a significant adva…

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

Rethinking Amodal Video Segmentation from Learning Supervised Signals with Object-centric Representation

Ke Fan, Jingshi Lei, Xuelin Qian +5

Video amodal segmentation is a particularly challenging task in computer vision, which requires to deduce the full shape of an object from the visible parts of it. Recently, some s…

cs.CV2023

Coarse-to-Fine Amodal Segmentation with Shape Prior

Jianxiong Gao, Xuelin Qian, Yikai Wang +4

Amodal object segmentation is a challenging task that involves segmenting both visible and occluded parts of an object. In this paper, we propose a novel approach, called Coarse-to…

cs.CV2023★ 3 cited

Rethinking Person Re-identification from a Projection-on-Prototypes Perspective

Qizao Wang, Xuelin Qian, Bin Li +2

Person Re-IDentification (Re-ID) as a retrieval task, has achieved tremendous development over the past decade. Existing state-of-the-art methods follow an analogous framework to f…

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.…

cs.CV2023★ 4 cited

Pushing the Limits of 3D Shape Generation at Scale

Yu Wang, Xuelin Qian, Jingyang Huo +3

We present a significant breakthrough in 3D shape generation by scaling it to unprecedented dimensions. Through the adaptation of the Auto-Regressive model and the utilization of l…

cs.CV2023

Learning Versatile 3D Shape Generation with Improved AR Models

Simian Luo, Xuelin Qian, Yanwei Fu +5

Auto-Regressive (AR) models have achieved impressive results in 2D image generation by modeling joint distributions in the grid space. While this approach has been extended to the…

cs.CV2023★ 2 cited

Joint fMRI Decoding and Encoding with Latent Embedding Alignment

Xuelin Qian, Yikai Wang, Yanwei Fu +3

The connection between brain activity and corresponding visual stimuli is crucial in comprehending the human brain. While deep generative models have exhibited advancement in recov…

cs.CV2022

DST: Dynamic Substitute Training for Data-free Black-box Attack

Wenxuan Wang, Xuelin Qian, Yanwei Fu +1

With the wide applications of deep neural network models in various computer vision tasks, more and more works study the model vulnerability to adversarial examples. For data-free…

cs.CV2022★ 1 cited

ImpDet: Exploring Implicit Fields for 3D Object Detection

Xuelin Qian, Li Wang, Yi Zhu +3

Conventional 3D object detection approaches concentrate on bounding boxes representation learning with several parameters, i.e., localization, dimension, and orientation. Despite i…

cs.CV2022★ 1 cited

QS-Craft: Learning to Quantize, Scrabble and Craft for Conditional Human Motion Animation

Yuxin Hong, Xuelin Qian, Simian Luo +2

This paper studies the task of conditional Human Motion Animation (cHMA). Given a source image and a driving video, the model should animate the new frame sequence, in which the pe…

cs.CV2020★ 5 cited

Long-Term Cloth-Changing Person Re-identification

Xuelin Qian, Wenxuan Wang, Li Zhang +5

Person re-identification (Re-ID) aims to match a target person across camera views at different locations and times. Existing Re-ID studies focus on the short-term cloth-consistent…

cs.CV2020★ 8 cited

When Person Re-identification Meets Changing Clothes

Fangbin Wan, Yang Wu, Xuelin Qian +2

Person re-identification (ReID) is now an active research topic for AI-based video surveillance applications such as specific person search, but the practical issue that the target…

cs.CV2018★ 32 cited

SCSP: Spectral Clustering Filter Pruning with Soft Self-adaption Manners

Huiyuan Zhuo, Xuelin Qian, Yanwei Fu +2

Deep Convolutional Neural Networks (CNN) has achieved significant success in computer vision field. However, the high computational cost of the deep complex models prevents the dep…