Search Results for author: Fei Shen

Found 25 papers, 12 papers with code

Long-Term TalkingFace Generation via Motion-Prior Conditional Diffusion Model

no code implementations13 Feb 2025 Fei Shen, Cong Wang, Junyao Gao, Qin Guo, Jisheng Dang, Jinhui Tang, Tat-Seng Chua

Recent advances in conditional diffusion models have shown promise for generating realistic TalkingFace videos, yet challenges persist in achieving consistent head movement, synchronized facial expressions, and accurate lip synchronization over extended generations.

motion prediction

Artificial Intelligence for Central Dogma-Centric Multi-Omics: Challenges and Breakthroughs

no code implementations17 Dec 2024 Lei Xin, Caiyun Huang, Hao Li, Shihong Huang, Yuling Feng, Zhenglun Kong, Zicheng Liu, Siyuan Li, Chang Yu, Fei Shen, Hao Tang

With the rapid development of high-throughput sequencing platforms, an increasing number of omics technologies, such as genomics, metabolomics, and transcriptomics, are being applied to disease genetics research.

Disease Prediction

DVP-MVS: Synergize Depth-Edge and Visibility Prior for Multi-View Stereo

no code implementations16 Dec 2024 Zhenlong Yuan, Jinguo Luo, Fei Shen, Zhaoxin Li, Cong Liu, Tianlu Mao, Zhaoqi Wang

Patch deformation-based methods have recently exhibited substantial effectiveness in multi-view stereo, due to the incorporation of deformable and expandable perception to reconstruct textureless areas.

Lesion-aware network for diabetic retinopathy diagnosis

1 code implementation14 Aug 2024 Xue Xia, Kun Zhan, Yuming Fang, Wenhui Jiang, Fei Shen

To this end, we propose a CNN-based DR diagnosis network with attention mechanism involved, termed lesion-aware network, to better capture lesion information from imbalanced data.

Lesion Segmentation

Few-shot Defect Image Generation based on Consistency Modeling

1 code implementation1 Aug 2024 Qingfeng Shi, Jing Wei, Fei Shen, Zhengtao Zhang

To address these issues, we propose DefectDiffu, a novel text-guided diffusion method to model both intra-product background consistency and inter-product defect consistency across multiple products and modulate the consistency perturbation directions to control product type and defect strength, achieving diversified defect image generation.

Defect Detection Diversity +1

MSP-MVS: Multi-Granularity Segmentation Prior Guided Multi-View Stereo

no code implementations27 Jul 2024 Zhenlong Yuan, Cong Liu, Fei Shen, Zhaoxin Li, Jinguo Luo, Tianlu Mao, Zhaoqi Wang

However, such methods mainly concentrate on searching for pixels without matching ambiguity (i. e., reliable pixels) when constructing deformed patches, while neglecting the deformation instability caused by unexpected edge-skipping, resulting in potential matching distortions.

IMAGDressing-v1: Customizable Virtual Dressing

1 code implementation17 Jul 2024 Fei Shen, Xin Jiang, Xin He, Hu Ye, Cong Wang, Xiaoyu Du, Zechao Li, Jinhui Tang

Latest advances have achieved realistic virtual try-on (VTON) through localized garment inpainting using latent diffusion models, significantly enhancing consumers' online shopping experience.

Denoising Image Generation +1

VCP-CLIP: A visual context prompting model for zero-shot anomaly segmentation

1 code implementation17 Jul 2024 Zhen Qu, Xian Tao, Mukesh Prasad, Fei Shen, Zhengtao Zhang, Xinyi Gong, Guiguang Ding

In this end, we propose a visual context prompting model (VCP-CLIP) for ZSAS task based on CLIP.

Ranked #6 on Anomaly Detection on VisA (Segmentation AUPRO metric, using extra training data)

Anomaly Detection Anomaly Segmentation +2

Boosting Consistency in Story Visualization with Rich-Contextual Conditional Diffusion Models

1 code implementation2 Jul 2024 Fei Shen, Hu Ye, Sibo Liu, Jun Zhang, Cong Wang, Xiao Han, Wei Yang

Moreover, RCDMs can generate consistent stories with a single forward inference compared to autoregressive models.

Story Visualization

V-Express: Conditional Dropout for Progressive Training of Portrait Video Generation

no code implementations4 Jun 2024 Cong Wang, Kuan Tian, Jun Zhang, Yonghang Guan, Feng Luo, Fei Shen, Zhiwei Jiang, Qing Gu, Xiao Han, Wei Yang

In our work on portrait video generation, we identified audio signals as particularly weak, often overshadowed by stronger signals such as facial pose and reference image.

Video Generation

Ensembling Diffusion Models via Adaptive Feature Aggregation

1 code implementation27 May 2024 Cong Wang, Kuan Tian, Yonghang Guan, Jun Zhang, Zhiwei Jiang, Fei Shen, Xiao Han, Qing Gu, Wei Yang

In this paper, we propose a novel ensembling method, Adaptive Feature Aggregation (AFA), which dynamically adjusts the contributions of multiple models at the feature level according to various states (i. e., prompts, initial noises, denoising steps, and spatial locations), thereby keeping the advantages of multiple diffusion models, while suppressing their disadvantages.

Denoising

LR-FPN: Enhancing Remote Sensing Object Detection with Location Refined Feature Pyramid Network

no code implementations2 Apr 2024 Hanqian Li, Ruinan Zhang, Ye Pan, Junchi Ren, Fei Shen

To address this, we propose a novel location refined feature pyramid network (LR-FPN) to enhance the extraction of shallow positional information and facilitate fine-grained context interaction.

Object object-detection +1

Low-Complexity Estimation Algorithm and Decoupling Scheme for FRaC System

no code implementations27 Mar 2024 Mengjiang Sun, Peng Chen, Zhenxin Cao, Fei Shen

Hence, a novel decomposed decoupled atomic norm minimization (DANM) method is proposed by splitting the 3D-parameter estimating matrix into multiple 2D matrices with sparsity constraints.

Autonomous Vehicles

Advancing Pose-Guided Image Synthesis with Progressive Conditional Diffusion Models

1 code implementation10 Oct 2023 Fei Shen, Hu Ye, Jun Zhang, Cong Wang, Xiao Han, Wei Yang

Specifically, in the first stage, we design a simple prior conditional diffusion model that predicts the global features of the target image by mining the global alignment relationship between pose coordinates and image appearance.

Image Generation

Investigating Shift Equivalence of Convolutional Neural Networks in Industrial Defect Segmentation

1 code implementation29 Sep 2023 Zhen Qu, Xian Tao, Fei Shen, Zhengtao Zhang, Tao Li

In industrial defect segmentation tasks, while pixel accuracy and Intersection over Union (IoU) are commonly employed metrics to assess segmentation performance, the output consistency (also referred to equivalence) of the model is often overlooked.

Data Augmentation Segmentation

The Second-place Solution for CVPR VISION 23 Challenge Track 1 -- Data Effificient Defect Detection

1 code implementation25 Jun 2023 Xian Tao, Zhen Qu, Hengliang Luo, Jianwen Han, Yonghao He, Danfeng Liu, Chengkan Lv, Fei Shen, Zhengtao Zhang

The Vision Challenge Track 1 for Data-Effificient Defect Detection requires competitors to instance segment 14 industrial inspection datasets in a data-defificient setting.

Defect Detection Instance Segmentation +2

Towards Total Online Unsupervised Anomaly Detection and Localization in Industrial Vision

no code implementations25 May 2023 Han Gao, Huiyuan Luo, Fei Shen, Zhengtao Zhang

Although existing image anomaly detection methods yield impressive results, they are mostly an offline learning paradigm that requires excessive data pre-collection, limiting their adaptability in industrial scenarios with online streaming data.

Contrastive Learning Unsupervised Anomaly Detection

Triplet Contrastive Representation Learning for Unsupervised Vehicle Re-identification

1 code implementation23 Jan 2023 Fei Shen, Xiaoyu Du, Liyan Zhang, Xiangbo Shu, Jinhui Tang

To address this problem, in this paper, we propose a simple Triplet Contrastive Representation Learning (TCRL) framework which leverages cluster features to bridge the part features and global features for unsupervised vehicle re-identification.

Contrastive Learning Representation Learning +3

HSGNet: Object Re-identification with Hierarchical Similarity Graph Network

no code implementations10 Nov 2022 Fei Shen, Mengwan Wei, Junchi Ren

Secondly, we divide the feature map along with the spatial and channel directions in each hierarchical graph.

Object

GiT: Graph Interactive Transformer for Vehicle Re-identification

no code implementations12 Jul 2021 Fei Shen, Yi Xie, Jianqing Zhu, Xiaobin Zhu, Huanqiang Zeng

In the macro view, a list of GiT blocks are stacked to build a vehicle re-identification model, in where graphs are to extract discriminative local features within patches and transformers are to extract robust global features among patches.

Person Re-Identification Vehicle Re-Identification

A Competitive Method to VIPriors Object Detection Challenge

no code implementations19 Apr 2021 Fei Shen, Xin He, Mengwan Wei, Yi Xie

In this report, we introduce the technical details of our submission to the VIPriors object detection challenge.

Data Augmentation Object +2

Exploring Spatial Significance via Hybrid Pyramidal Graph Network for Vehicle Re-identification

1 code implementation29 May 2020 Fei Shen, Jianqing Zhu, Xiaobin Zhu, Yi Xie, Jingchang Huang

Secondly, a novel pyramidal graph network (PGN) is designed to comprehensively explore the spatial significance of feature maps at multiple scales.

Vehicle Re-Identification

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