Search Results for author: Yongyong Chen

Found 10 papers, 0 papers with code

DiffSCI: Zero-Shot Snapshot Compressive Imaging via Iterative Spectral Diffusion Model

no code implementations19 Nov 2023 Zhenghao Pan, Haijin Zeng, JieZhang Cao, Kai Zhang, Yongyong Chen

Specifically, firstly, we employ a pre-trained diffusion model, which has been trained on a substantial corpus of RGB images, as the generative denoiser within the Plug-and-Play framework for the first time.


MSFA-Frequency-Aware Transformer for Hyperspectral Images Demosaicing

no code implementations23 Mar 2023 Haijin Zeng, Kai Feng, Shaoguang Huang, JieZhang Cao, Yongyong Chen, Hongyan zhang, Hiep Luong, Wilfried Philips

The advantage of Maformer is that it can leverage the MSFA information and non-local dependencies present in the data.


How Image Generation Helps Visible-to-Infrared Person Re-Identification?

no code implementations4 Oct 2022 Honghu Pan, Yongyong Chen, Yunqi He, Xin Li, Zhenyu He

To this end, we propose Flow2Flow, a unified framework that could jointly achieve training sample expansion and cross-modality image generation for V2I person ReID.

Image Generation Person Re-Identification

Towards Complete-View and High-Level Pose-based Gait Recognition

no code implementations23 Sep 2022 Honghu Pan, Yongyong Chen, Tingyang Xu, Yunqi He, Zhenyu He

Extensive experiments on two large gait recognition datasets, i. e., CASIA-B and OUMVLP-Pose, demonstrate that our method outperforms the baseline model and existing pose-based methods by a large margin.

Gait Recognition Generative Adversarial Network +1

Multi-Granularity Graph Pooling for Video-based Person Re-Identification

no code implementations23 Sep 2022 Honghu Pan, Yongyong Chen, Zhenyu He

To downsample the graph, we propose a multi-head full attention graph pooling (MHFAPool) layer, which integrates the advantages of existing node clustering and node selection pooling methods.

Node Clustering Retrieval +2

Pose-Aided Video-based Person Re-Identification via Recurrent Graph Convolutional Network

no code implementations23 Sep 2022 Honghu Pan, Qiao Liu, Yongyong Chen, Yunqi He, Yuan Zheng, Feng Zheng, Zhenyu He

Finally, we propose a dual-attention method consisting of node-attention and time-attention to obtain the temporal graph representation from the node embeddings, where the self-attention mechanism is employed to learn the importance of each node and each frame.

Retrieval Video-Based Person Re-Identification +1

Low-rank Meets Sparseness: An Integrated Spatial-Spectral Total Variation Approach to Hyperspectral Denoising

no code implementations27 Apr 2022 Haijin Zeng, Shaoguang Huang, Yongyong Chen, Hiep Luong, Wilfried Philips

Based on this fact, we propose a novel TV regularization to simultaneously characterize the sparsity and low-rank priors of the gradient map (LRSTV).


Log-based Sparse Nonnegative Matrix Factorization for Data Representation

no code implementations22 Apr 2022 Chong Peng, Yiqun Zhang, Yongyong Chen, Zhao Kang, Chenglizhao Chen, Qiang Cheng

Nonnegative matrix factorization (NMF) has been widely studied in recent years due to its effectiveness in representing nonnegative data with parts-based representations.

Hyperspectral Image Denoising Using Non-convex Local Low-rank and Sparse Separation with Spatial-Spectral Total Variation Regularization

no code implementations8 Jan 2022 Chong Peng, Yang Liu, Yongyong Chen, Xinxin Wu, Andrew Cheng, Zhao Kang, Chenglizhao Chen, Qiang Cheng

In this paper, we propose a novel nonconvex approach to robust principal component analysis for HSI denoising, which focuses on simultaneously developing more accurate approximations to both rank and column-wise sparsity for the low-rank and sparse components, respectively.

Hyperspectral Image Denoising Image Denoising

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