45 citations · 196 across the 27 of their papers we have counts for
28 papers
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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.…
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…
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…
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…
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…
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…
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…
M3Lung-Sys: A Deep Learning System for Multi-Class Lung Pneumonia Screening from CT Imaging
Xuelin Qian, Huazhu Fu, Weiya Shi +4
To counter the outbreak of COVID-19, the accurate diagnosis of suspected cases plays a crucial role in timely quarantine, medical treatment, and preventing the spread of the pandem…
A New Screening Method for COVID-19 based on Ocular Feature Recognition by Machine Learning Tools
Yanwei Fu, Feng Li, Wenxuan Wang +4
The Coronavirus disease 2019 (COVID-19) has affected several million people. With the outbreak of the epidemic, many researchers are devoting themselves to the COVID-19 screening s…
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…