Search Results for author: Xuelin Qian

Found 24 papers, 4 papers with code

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

no code implementations27 Mar 2024 Jingyang Huo, Yikai Wang, Xuelin Qian, Yun Wang, Chong Li, Jianfeng Feng, Yanwei Fu

Recent fMRI-to-image approaches mainly focused on associating fMRI signals with specific conditions of pre-trained diffusion models.

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

no code implementations19 Feb 2024 Xuelin Qian, Yu Wang, Simian Luo, yinda zhang, Ying Tai, Zhenyu Zhang, Chengjie Wang, xiangyang xue, Bo Zhao, Tiejun Huang, Yunsheng Wu, Yanwei Fu

In this paper, we extend auto-regressive models to 3D domains, and seek a stronger ability of 3D shape generation by improving auto-regressive models at capacity and scalability simultaneously.

3D Shape Generation Image Generation +1

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

no code implementations12 Dec 2023 Jianxiong Gao, Yuqian Fu, Yun Wang, Xuelin Qian, Jianfeng Feng, Yanwei Fu

In this paper, we introduce Recon3DMind, an innovative task aimed at reconstructing 3D visuals from Functional Magnetic Resonance Imaging (fMRI) signals, marking a significant advancement in the fields of cognitive neuroscience and computer vision.

Brain Decoding valid

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

no code implementations1 Nov 2023 Xuelin Qian, Yun Wang, Jingyang Huo, Jianfeng Feng, Yanwei Fu

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 diagnostics, and virtual reality.

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

1 code implementation ICCV 2023 Ke Fan, Jingshi Lei, Xuelin Qian, Miaopeng Yu, Tianjun Xiao, Tong He, Zheng Zhang, Yanwei Fu

Furthermore, we propose a multi-view fusion layer based temporal module which is equipped with a set of object slots and interacts with features from different views by attention mechanism to fulfill sufficient object representation completion.

Object Video Segmentation +1

Coarse-to-Fine Amodal Segmentation with Shape Prior

1 code implementation ICCV 2023 Jianxiong Gao, Xuelin Qian, Yikai Wang, Tianjun Xiao, Tong He, Zheng Zhang, Yanwei Fu

To address this issue, we propose a convolution refine module to inject fine-grained information and provide a more precise amodal object segmentation based on visual features and coarse-predicted segmentation.

Object Segmentation +1

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

no code implementations21 Aug 2023 Qizao Wang, Xuelin Qian, Bin Li, Yanwei Fu, xiangyang xue

In this paper, we rethink the role of the classifier in person Re-ID, and advocate a new perspective to conceive the classifier as a projection from image features to class prototypes.

Person Re-Identification Person Retrieval +1

Pushing the Limits of 3D Shape Generation at Scale

no code implementations20 Jun 2023 Yu Wang, Xuelin Qian, Jingyang Huo, Tiejun Huang, Bo Zhao, Yanwei Fu

Through the adaptation of the Auto-Regressive model and the utilization of large language models, we have developed a remarkable model with an astounding 3. 6 billion trainable parameters, establishing it as the largest 3D shape generation model to date, named Argus-3D.

3D Shape Generation Quantization +1

Joint fMRI Decoding and Encoding with Latent Embedding Alignment

no code implementations26 Mar 2023 Xuelin Qian, Yikai Wang, Yanwei Fu, Xinwei Sun, xiangyang xue, Jianfeng Feng

Our Latent Embedding Alignment (LEA) model concurrently recovers visual stimuli from fMRI signals and predicts brain activity from images within a unified framework.

Image Generation

Learning Versatile 3D Shape Generation with Improved AR Models

no code implementations26 Mar 2023 Simian Luo, Xuelin Qian, Yanwei Fu, yinda zhang, Ying Tai, Zhenyu Zhang, Chengjie Wang, xiangyang xue

Auto-Regressive (AR) models have achieved impressive results in 2D image generation by modeling joint distributions in the grid space.

3D Shape Generation Image Generation +1

Co-Attention Aligned Mutual Cross-Attention for Cloth-Changing Person Re-Identification

1 code implementation Asian Conference on Computer Vision (ACCV) 2023 Qizao Wang, Xuelin Qian, Yanwei Fu, xiangyang xue

In this paper, we first design a novel Shape Semantics Embedding (SSE) module to encode body shape semantic information, which is one of the essential clues to distinguish pedestrians when their clothes change.

Cloth-Changing Person Re-Identification Person Retrieval +1

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

no code implementations CVPR 2022 Wenxuan Wang, Xuelin Qian, Yanwei Fu, xiangyang xue

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.

Knowledge Distillation

ImpDet: Exploring Implicit Fields for 3D Object Detection

no code implementations31 Mar 2022 Xuelin Qian, Li Wang, Yi Zhu, Li Zhang, Yanwei Fu, xiangyang xue

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

3D Object Detection Object +2

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

no code implementations22 Mar 2022 Yuxin Hong, Xuelin Qian, Simian Luo, xiangyang xue, Yanwei Fu

To this end, this paper proposes a novel model of learning to Quantize, Scrabble, and Craft (QS-Craft) for conditional human motion animation.

Generative Adversarial Network

M3Lung-Sys: A Deep Learning System for Multi-Class Lung Pneumonia Screening from CT Imaging

no code implementations7 Oct 2020 Xuelin Qian, Huazhu Fu, Weiya Shi, Tao Chen, Yanwei Fu, Fei Shan, xiangyang xue

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 pandemic.

A New Screening Method for COVID-19 based on Ocular Feature Recognition by Machine Learning Tools

no code implementations4 Sep 2020 Yanwei Fu, Feng Li, Wenxuan Wang, Haicheng Tang, Xuelin Qian, Mengwei Gu, xiangyang xue

After more than four months study, we found that the confirmed cases of COVID-19 present the consistent ocular pathological symbols; and we propose a new screening method of analyzing the eye-region images, captured by common CCD and CMOS cameras, could reliably make a rapid risk screening of COVID-19 with very high accuracy.

BIG-bench Machine Learning Ethics +2

Long-Term Cloth-Changing Person Re-identification

no code implementations26 May 2020 Xuelin Qian, Wenxuan Wang, Li Zhang, Fangrui Zhu, Yanwei Fu, Tao Xiang, Yu-Gang Jiang, xiangyang xue

Specifically, we consider that under cloth-changes, soft-biometrics such as body shape would be more reliable.

Cloth-Changing Person Re-Identification

When Person Re-identification Meets Changing Clothes

no code implementations9 Mar 2020 Fangbin Wan, Yang Wu, Xuelin Qian, Yixiong Chen, Yanwei Fu

We find that changing clothes makes ReID a much harder problem in the sense of bringing difficulties to learning effective representations and also challenges the generalization ability of previous ReID models to identify persons with unseen (new) clothes.

Person Re-Identification Person Search

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

no code implementations14 Jun 2018 Huiyuan Zhuo, Xuelin Qian, Yanwei Fu, Heng Yang, xiangyang xue

In this paper, we proposed a novel filter pruning for convolutional neural networks compression, namely spectral clustering filter pruning with soft self-adaption manners (SCSP).

Clustering Model Compression

Pose-Normalized Image Generation for Person Re-identification

2 code implementations ECCV 2018 Xuelin Qian, Yanwei Fu, Tao Xiang, Wenxuan Wang, Jie Qiu, Yang Wu, Yu-Gang Jiang, xiangyang xue

Person Re-identification (re-id) faces two major challenges: the lack of cross-view paired training data and learning discriminative identity-sensitive and view-invariant features in the presence of large pose variations.

Generative Adversarial Network Image Generation +2

Multi-scale Deep Learning Architectures for Person Re-identification

no code implementations ICCV 2017 Xuelin Qian, Yanwei Fu, Yu-Gang Jiang, Tao Xiang, xiangyang xue

Our model is able to learn deep discriminative feature representations at different scales and automatically determine the most suitable scales for matching.

Person Re-Identification

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