Search Results for author: Xin Yuan

Found 119 papers, 45 papers with code

BIRNAT: Bidirectional Recurrent Neural Networks with Adversarial Training for Video Snapshot Compressive Imaging

1 code implementation ECCV 2020 Ziheng Cheng, Ruiying Lu, Zhengjue Wang, Hao Zhang, Bo Chen, Ziyi Meng, Xin Yuan

This measurement and the modulation masks are fed into our Recurrent Neural Network (RNN) to reconstruct the desired high-speed frames.

Dual-Scale Transformer for Large-Scale Single-Pixel Imaging

1 code implementation7 Apr 2024 Gang Qu, Ping Wang, Xin Yuan

In this paper, we propose a deep unfolding network with hybrid-attention Transformer on Kronecker SPI model, dubbed HATNet, to improve the imaging quality of real SPI cameras.


Binarized Low-light Raw Video Enhancement

1 code implementation29 Mar 2024 Gengchen Zhang, Yulun Zhang, Xin Yuan, Ying Fu

For the second issue, we present a distribution-aware binary convolution, which captures the distribution characteristics of real-valued input and incorporates them into plain binary convolutions to alleviate the degradation in performance.

Denoising Video Enhancement

SCINeRF: Neural Radiance Fields from a Snapshot Compressive Image

1 code implementation29 Mar 2024 Yunhao Li, Xiaodong Wang, Ping Wang, Xin Yuan, Peidong Liu

SCI is a cost-effective method that enables the recording of high-dimensional data, such as hyperspectral or temporal information, into a single image using low-cost 2D imaging sensors.

Image Generation Image Reconstruction

A First Look at GPT Apps: Landscape and Vulnerability

no code implementations23 Feb 2024 Zejun Zhang, Li Zhang, Xin Yuan, Anlan Zhang, Mengwei Xu, Feng Qian

With the advancement of Large Language Models (LLMs), increasingly sophisticated and powerful GPTs are entering the market.

Failure Analysis in Next-Generation Critical Cellular Communication Infrastructures

no code implementations6 Feb 2024 Siguo Bi, Xin Yuan, Shuyan Hu, Kai Li, Wei Ni, Ekram Hossain, Xin Wang

The advent of communication technologies marks a transformative phase in critical infrastructure construction, where the meticulous analysis of failures becomes paramount in achieving the fundamental objectives of continuity, security, and availability.

Inflation with Diffusion: Efficient Temporal Adaptation for Text-to-Video Super-Resolution

no code implementations18 Jan 2024 Xin Yuan, Jinoo Baek, Keyang Xu, Omer Tov, Hongliang Fei

We propose an efficient diffusion-based text-to-video super-resolution (SR) tuning approach that leverages the readily learned capacity of pixel level image diffusion model to capture spatial information for video generation.

Video Generation Video Super-Resolution

SnapCap: Efficient Snapshot Compressive Video Captioning

no code implementations10 Jan 2024 JianQiao Sun, Yudi Su, Hao Zhang, Ziheng Cheng, Zequn Zeng, Zhengjue Wang, Bo Chen, Xin Yuan

To address these problems, in this paper, we propose a novel VC pipeline to generate captions directly from the compressed measurement, which can be captured by a snapshot compressive sensing camera and we dub our model SnapCap.

Compressive Sensing Video Captioning

Mobility and Cost Aware Inference Accelerating Algorithm for Edge Intelligence

no code implementations27 Dec 2023 Xin Yuan, Ning li, Kang Wei, Wenchao Xu, Quan Chen, Hao Chen, Song Guo

The model segmentation without user mobility has been investigated deeply by previous works.


Group Multi-View Transformer for 3D Shape Analysis with Spatial Encoding

no code implementations27 Dec 2023 Lixiang Xu, Qingzhe Cui, Richang Hong, Wei Xu, Enhong Chen, Xin Yuan, Chenglong Li, Yuanyan Tang

The large model GMViT achieves excellent 3D classification and retrieval results on the benchmark datasets ModelNet, ShapeNetCore55, and MCB.

3D Classification 3D Shape Recognition +2

High Efficiency Inference Accelerating Algorithm for NOMA-based Mobile Edge Computing

no code implementations26 Dec 2023 Xin Yuan, Ning li, Tuo Zhang, Muqing Li, YuWen Chen, Jose Fernan Martinez Ortega, Song Guo

Specifically, when the mobile user has a large model inference task needed to be calculated in the NOMA-based MEC, it will take the energy consumption of both device and edge server and the inference latency into account to find the optimal model split strategy, subchannel allocation strategy (uplink and downlink), and transmission power allocation strategy (uplink and downlink).


Data-Agnostic Model Poisoning against Federated Learning: A Graph Autoencoder Approach

no code implementations30 Nov 2023 Kai Li, Jingjing Zheng, Xin Yuan, Wei Ni, Ozgur B. Akan, H. Vincent Poor

The attacker then adversarially regenerates the graph structural correlations while maximizing the FL training loss, and subsequently generates malicious local models using the adversarial graph structure and the training data features of the benign ones.

Federated Learning Model Poisoning

OFDMA-F$^2$L: Federated Learning With Flexible Aggregation Over an OFDMA Air Interface

no code implementations25 Nov 2023 Shuyan Hu, Xin Yuan, Wei Ni, Xin Wang, Ekram Hossain, H. Vincent Poor

Federated learning (FL) can suffer from a communication bottleneck when deployed in mobile networks, limiting participating clients and deterring FL convergence.

Federated Learning

Latent Diffusion Prior Enhanced Deep Unfolding for Spectral Image Reconstruction

no code implementations24 Nov 2023 Zongliang Wu, Ruiying Lu, Ying Fu, Xin Yuan

Snapshot compressive spectral imaging reconstruction aims to reconstruct three-dimensional spatial-spectral images from a single-shot two-dimensional compressed measurement.

Computational Efficiency Image Reconstruction +1

Image Super-Resolution with Text Prompt Diffusion

1 code implementation24 Nov 2023 Zheng Chen, Yulun Zhang, Jinjin Gu, Xin Yuan, Linghe Kong, Guihai Chen, Xiaokang Yang

Specifically, we first design a text-image generation pipeline to integrate text into the SR dataset through the text degradation representation and degradation model.

Image Generation Image Super-Resolution +1

Binarized 3D Whole-body Human Mesh Recovery

1 code implementation24 Nov 2023 Zhiteng Li, Yulun Zhang, Jing Lin, Haotong Qin, Jinjin Gu, Xin Yuan, Linghe Kong, Xiaokang Yang

In this work, we propose a Binarized Dual Residual Network (BiDRN), a novel quantization method to estimate the 3D human body, face, and hands parameters efficiently.

Binarization Human Mesh Recovery +1

Support or Refute: Analyzing the Stance of Evidence to Detect Out-of-Context Mis- and Disinformation

no code implementations3 Nov 2023 Xin Yuan, Jie Guo, Weidong Qiu, Zheng Huang, Shujun Li

Mis- and disinformation online have become a major societal problem as major sources of online harms of different kinds.

Factorized Diffusion Architectures for Unsupervised Image Generation and Segmentation

no code implementations27 Sep 2023 Xin Yuan, Michael Maire

We develop a neural network architecture which, trained in an unsupervised manner as a denoising diffusion model, simultaneously learns to both generate and segment images.

Denoising Image Generation +4

Mobile Foundation Model as Firmware

1 code implementation28 Aug 2023 Jinliang Yuan, Chen Yang, Dongqi Cai, Shihe Wang, Xin Yuan, Zeling Zhang, Xiang Li, Dingge Zhang, Hanzi Mei, Xianqing Jia, Shangguang Wang, Mengwei Xu

Concurrently, each app contributes a concise, offline fine-tuned "adapter" tailored to distinct downstream tasks.

Spatial-Frequency U-Net for Denoising Diffusion Probabilistic Models

no code implementations27 Jul 2023 Xin Yuan, Linjie Li, JianFeng Wang, Zhengyuan Yang, Kevin Lin, Zicheng Liu, Lijuan Wang

In this paper, we study the denoising diffusion probabilistic model (DDPM) in wavelet space, instead of pixel space, for visual synthesis.


Towards Ubiquitous Semantic Metaverse: Challenges, Approaches, and Opportunities

no code implementations13 Jul 2023 Kai Li, Billy Pik Lik Lau, Xin Yuan, Wei Ni, Mohsen Guizani, Chau Yuen

In recent years, ubiquitous semantic Metaverse has been studied to revolutionize immersive cyber-virtual experiences for augmented reality (AR) and virtual reality (VR) users, which leverages advanced semantic understanding and representation to enable seamless, context-aware interactions within mixed-reality environments.

Marketing Mixed Reality

Unfolding Framework with Prior of Convolution-Transformer Mixture and Uncertainty Estimation for Video Snapshot Compressive Imaging

no code implementations ICCV 2023 Siming Zheng, Xin Yuan

We consider the problem of video snapshot compressive imaging (SCI), where sequential high-speed frames are modulated by different masks and captured by a single measurement.

Cooperative Hardware-Prompt Learning for Snapshot Compressive Imaging

no code implementations1 Jun 2023 Jiamian Wang, Zongliang Wu, Yulun Zhang, Xin Yuan, Tao Lin, Zhiqiang Tao

In this work, we tackle this challenge by marrying prompt tuning with FL to snapshot compressive imaging for the first time and propose an federated hardware-prompt learning (FedHP) method.

Federated Learning

Hierarchical Integration Diffusion Model for Realistic Image Deblurring

1 code implementation NeurIPS 2023 Zheng Chen, Yulun Zhang, Ding Liu, Bin Xia, Jinjin Gu, Linghe Kong, Xin Yuan

Specifically, we perform the DM in a highly compacted latent space to generate the prior feature for the deblurring process.

Deblurring Image Deblurring +1

Binarized Spectral Compressive Imaging

2 code implementations NeurIPS 2023 Yuanhao Cai, Yuxin Zheng, Jing Lin, Xin Yuan, Yulun Zhang, Haoqian Wang

Finally, our BiSRNet is derived by using the proposed techniques to binarize the base model.


EfficientSCI: Densely Connected Network with Space-time Factorization for Large-scale Video Snapshot Compressive Imaging

1 code implementation CVPR 2023 Lishun Wang, Miao Cao, Xin Yuan

We are the first time to show that an UHD color video with high compression ratio can be reconstructed from a snapshot 2D measurement using a single end-to-end deep learning model with PSNR above 32 dB.

Learn to Unlearn: A Survey on Machine Unlearning

no code implementations12 May 2023 Youyang Qu, Xin Yuan, Ming Ding, Wei Ni, Thierry Rakotoarivelo, David Smith

This inspired recent research on removing the influence of specific data samples from a trained ML model.

Fairness Machine Unlearning

New Adversarial Image Detection Based on Sentiment Analysis

1 code implementation3 May 2023 Yulong Wang, Tianxiang Li, Shenghong Li, Xin Yuan, Wei Ni

Deep Neural Networks (DNNs) are vulnerable to adversarial examples, while adversarial attack models, e. g., DeepFool, are on the rise and outrunning adversarial example detection techniques.

Adversarial Attack Sentiment Analysis

Adversarial Attacks and Defenses in Machine Learning-Powered Networks: A Contemporary Survey

no code implementations11 Mar 2023 Yulong Wang, Tong Sun, Shenghong Li, Xin Yuan, Wei Ni, Ekram Hossain, H. Vincent Poor

This survey provides a comprehensive overview of the recent advancements in the field of adversarial attack and defense techniques, with a focus on deep neural network-based classification models.

Adversarial Attack Adversarial Defense

Amplitude-Varying Perturbation for Balancing Privacy and Utility in Federated Learning

no code implementations7 Mar 2023 Xin Yuan, Wei Ni, Ming Ding, Kang Wei, Jun Li, H. Vincent Poor

The contribution of the new DP mechanism to the convergence and accuracy of privacy-preserving FL is corroborated, compared to the state-of-the-art Gaussian noise mechanism with a persistent noise amplitude.

Federated Learning Privacy Preserving

RIS-Assisted Jamming Rejection and Path Planning for UAV-Borne IoT Platform: A New Deep Reinforcement Learning Framework

no code implementations10 Feb 2023 Shuyan Hu, Xin Yuan, Wei Ni, Xin Wang, Abbas Jamalipour

This paper presents a new deep reinforcement learning (DRL)-based approach to the trajectory planning and jamming rejection of an unmanned aerial vehicle (UAV) for the Internet-of-Things (IoT) applications.

Trajectory Planning

Universal Domain Adaptation for Remote Sensing Image Scene Classification

1 code implementation26 Jan 2023 Qingsong Xu, Yilei Shi, Xin Yuan, Xiao Xiang Zhu

Empirical results show that the proposed model is effective and practical for remote sensing image scene classification, regardless of whether the source data is available or not.

Classification Image Classification +3

Large-scale Global Low-rank Optimization for Computational Compressed Imaging

no code implementations8 Jan 2023 Daoyu Li, Hanwen Xu, Miao Cao, Xin Yuan, David J. Brady, Liheng Bian

However, the computational cost has inhibited NLR from seeking global structural similarity, which consequentially keeps it trapped in the tradeoff between accuracy and efficiency and prevents it from high-dimensional large-scale tasks.

Demosaicking Patch Matching

Cross Aggregation Transformer for Image Restoration

3 code implementations24 Nov 2022 Zheng Chen, Yulun Zhang, Jinjin Gu, Yongbing Zhang, Linghe Kong, Xin Yuan

The core of our CAT is the Rectangle-Window Self-Attention (Rwin-SA), which utilizes horizontal and vertical rectangle window attention in different heads parallelly to expand the attention area and aggregate the features cross different windows.

Image Restoration Inductive Bias

Accurate Image Restoration with Attention Retractable Transformer

1 code implementation4 Oct 2022 Jiale Zhang, Yulun Zhang, Jinjin Gu, Yongbing Zhang, Linghe Kong, Xin Yuan

This is considered as a dense attention strategy since the interactions of tokens are restrained in dense regions.

Denoising Image Restoration +2

S^2-Transformer for Mask-Aware Hyperspectral Image Reconstruction

1 code implementation24 Sep 2022 Jiamian Wang, Kunpeng Li, Yulun Zhang, Xin Yuan, Zhiqiang Tao

By observing this physical encoding procedure, two major challenges stand in the way of a high-fidelity reconstruction.

Blocking Image Reconstruction

Spatial-Temporal Transformer for Video Snapshot Compressive Imaging

1 code implementation4 Sep 2022 Lishun Wang, Miao Cao, Yong Zhong, Xin Yuan

In this paper, we consider the reconstruction algorithm in video SCI, i. e., recovering a series of video frames from a compressed measurement.

Video Reconstruction

Dispersed Pixel Perturbation-based Imperceptible Backdoor Trigger for Image Classifier Models

no code implementations19 Aug 2022 Yulong Wang, Minghui Zhao, Shenghong Li, Xin Yuan, Wei Ni

In this paper, we propose a new backdoor trigger, which is easy to generate, imperceptible, and highly effective.

Text-to-Image Generation via Implicit Visual Guidance and Hypernetwork

no code implementations17 Aug 2022 Xin Yuan, Zhe Lin, Jason Kuen, Jianming Zhang, John Collomosse

We develop an approach for text-to-image generation that embraces additional retrieval images, driven by a combination of implicit visual guidance loss and generative objectives.

Retrieval Text-to-Image Generation

Trajectory Planning of Cellular-Connected UAV for Communication-assisted Radar Sensing

no code implementations27 Jul 2022 Shuyan Hu, Xin Yuan, Wei Ni, Xin Wang

Being a key technology for beyond fifth-generation wireless systems, joint communication and radar sensing (JCAS) utilizes the reflections of communication signals to detect foreign objects and deliver situational awareness.

Trajectory Planning

Degradation-Aware Unfolding Half-Shuffle Transformer for Spectral Compressive Imaging

1 code implementation20 May 2022 Yuanhao Cai, Jing Lin, Haoqian Wang, Xin Yuan, Henghui Ding, Yulun Zhang, Radu Timofte, Luc van Gool

In coded aperture snapshot spectral compressive imaging (CASSI) systems, hyperspectral image (HSI) reconstruction methods are employed to recover the spatial-spectral signal from a compressed measurement.

Compressive Sensing Image Reconstruction +1

AdaVocoder: Adaptive Vocoder for Custom Voice

no code implementations18 Mar 2022 Xin Yuan, Yongbing Feng, Mingming Ye, Cheng Tuo, Minghang Zhang

The solution to constructing a custom voice is to combine an adaptive acoustic model with a robust vocoder.

Speech Synthesis Transfer Learning

Learning Nonlocal Sparse and Low-Rank Models for Image Compressive Sensing

1 code implementation17 Mar 2022 Zhiyuan Zha, Bihan Wen, Xin Yuan, Saiprasad Ravishankar, Jiantao Zhou, Ce Zhu

Furthermore, we present a unified framework for incorporating various GSR and LR models and discuss the relationship between GSR and LR models.

Compressive Sensing

Coarse-to-Fine Sparse Transformer for Hyperspectral Image Reconstruction

1 code implementation9 Mar 2022 Yuanhao Cai, Jing Lin, Xiaowan Hu, Haoqian Wang, Xin Yuan, Yulun Zhang, Radu Timofte, Luc van Gool

Many algorithms have been developed to solve the inverse problem of coded aperture snapshot spectral imaging (CASSI), i. e., recovering the 3D hyperspectral images (HSIs) from a 2D compressive measurement.

Compressive Sensing Image Reconstruction +1

Motion-aware Dynamic Graph Neural Network for Video Compressive Sensing

no code implementations1 Mar 2022 Ruiying Lu, Ziheng Cheng, Bo Chen, Xin Yuan

Video snapshot compressive imaging (SCI) utilizes a 2D detector to capture sequential video frames and compresses them into a single measurement.

Compressive Sensing Video Compressive Sensing

Ensemble learning priors unfolding for scalable Snapshot Compressive Sensing

1 code implementation25 Jan 2022 Chengshuai Yang, Shiyu Zhang, Xin Yuan

To address these problems, we develop the ensemble learning priors to further improve the reconstruction accuracy and propose the scalable learning to empower deep learning the scalability just like the traditional algorithm.

Compressive Sensing Ensemble Learning

Deep Equilibrium Models for Video Snapshot Compressive Imaging

1 code implementation18 Jan 2022 Yaping Zhao, Siming Zheng, Xin Yuan

The ability of snapshot compressive imaging (SCI) systems to efficiently capture high-dimensional (HD) data has led to an inverse problem, which consists of recovering the HD signal from the compressed and noisy measurement.

Two-Stage is Enough: A Concise Deep Unfolding Reconstruction Network for Flexible Video Compressive Sensing

1 code implementation15 Jan 2022 Siming Zheng, Xiaoyu Yang, Xin Yuan

We consider the reconstruction problem of video compressive sensing (VCS) under the deep unfolding/rolling structure.

Compressive Sensing Demosaicking +1

Spectral Compressive Imaging Reconstruction Using Convolution and Contextual Transformer

1 code implementation15 Jan 2022 Lishun Wang, Zongliang Wu, Yong Zhong, Xin Yuan

Spectral compressive imaging (SCI) is able to encode the high-dimensional hyperspectral image to a 2D measurement, and then uses algorithms to reconstruct the spatio-spectral data-cube.

Inductive Bias

Adaptive Deep PnP Algorithm for Video Snapshot Compressive Imaging

1 code implementation14 Jan 2022 Zongliang Wu, Chengshuai Yang, Xiongfei Su, Xin Yuan

Towards this end, in this work, we propose the online PnP algorithm which can adaptively update the network's parameters within the PnP iteration; this makes the denoising network more applicable to the desired data in the SCI reconstruction.

Demosaicking Denoising

Modeling Mask Uncertainty in Hyperspectral Image Reconstruction

1 code implementation31 Dec 2021 Jiamian Wang, Yulun Zhang, Xin Yuan, Ziyi Meng, Zhiqiang Tao

Recently, hyperspectral imaging (HSI) has attracted increasing research attention, especially for the ones based on a coded aperture snapshot spectral imaging (CASSI) system.

Bilevel Optimization Image Reconstruction

Nonlinear Intensity Underwater Sonar Image Matching Method Based on Phase Information and Deep Convolution Features

no code implementations29 Nov 2021 Xiaoteng Zhou, Changli Yu, Xin Yuan, Haijun Feng, Yang Xu

In the field of deep-sea exploration, sonar is presently the only efficient long-distance sensing device.

Nonlinear Intensity Sonar Image Matching based on Deep Convolution Features

no code implementations17 Nov 2021 Xiaoteng Zhou, Changli Yu, Xin Yuan, Yi Wu, Haijun Feng, Citong Luo

In the field of deep-sea exploration, sonar is presently the only efficient long-distance sensing device.


no code implementations29 Sep 2021 Jiamian Wang, Yulun Zhang, Xin Yuan, Yun Fu, Zhiqiang Tao

As the inverse process of snapshot compressive imaging, the hyperspectral image (HSI) reconstruction takes the 2D measurement as input and posteriorly retrieves the captured 3D spatial-spectral signal.

Computational Efficiency Image Reconstruction

Computational Imaging and Artificial Intelligence: The Next Revolution of Mobile Vision

no code implementations18 Sep 2021 Jinli Suo, Weihang Zhang, Jin Gong, Xin Yuan, David J. Brady, Qionghai Dai

Signal capture stands in the forefront to perceive and understand the environment and thus imaging plays the pivotal role in mobile vision.

Decision Making Edge-computing

Dual-view Snapshot Compressive Imaging via Optical Flow Aided Recurrent Neural Network

1 code implementation11 Sep 2021 Ruiying Lu, Bo Chen, Guanliang Liu, Ziheng Cheng, Mu Qiao, Xin Yuan

In this paper, we propose an optical flow-aided recurrent neural network for dual video SCI systems, which provides high-quality decoding in seconds.

Compressive Sensing Optical Flow Estimation

Self-supervised Neural Networks for Spectral Snapshot Compressive Imaging

1 code implementation ICCV 2021 Ziyi Meng, Zhenming Yu, Kun Xu, Xin Yuan

In this paper, inspired by the untrained neural networks such as deep image priors (DIP) and deep decoders, we develop a framework by integrating DIP into the plug-and-play regime, leading to a self-supervised network for spectral SCI reconstruction.


Matching Underwater Sonar Images by the Learned Descriptor Based on Style Transfer Method

no code implementations27 Aug 2021 Xiaoteng Zhou, Changli Yu, Xin Yuan, Citong Luo

This paper proposes a method that combines the style transfer technique and the learned descriptor to enhance the matching performances of underwater sonar images.

Style Transfer

A Matching Algorithm based on Image Attribute Transfer and Local Features for Underwater Acoustic and Optical Images

no code implementations27 Aug 2021 Xiaoteng Zhou, Changli Yu, Xin Yuan, Citong Luo

Additionally, the method is based on the combination of image depth semantic layer, and it could indirectly display the local feature matching relationship between original image pair, which provides a new solution to the underwater multi-sensor image matching problem.


Deep Denoising Method for Side Scan Sonar Images without High-quality Reference Data

no code implementations27 Aug 2021 Xiaoteng Zhou, Changli Yu, Xin Yuan, Citong Luo

Subsea images measured by the side scan sonars (SSSs) are necessary visual data in the process of deep-sea exploration by using the autonomous underwater vehicles (AUVs).


A Simple and Efficient Reconstruction Backbone for Snapshot Compressive Imaging

1 code implementation17 Aug 2021 Jiamian Wang, Yulun Zhang, Xin Yuan, Yun Fu, Zhiqiang Tao

The emerging technology of snapshot compressive imaging (SCI) enables capturing high dimensional (HD) data in an efficient way.

Compressive Sensing Computational Efficiency +4

10-mega pixel snapshot compressive imaging with a hybrid coded aperture

1 code implementation30 Jun 2021 Zhihong Zhang, Chao Deng, Yang Liu, Xin Yuan, Jinli Suo, Qionghai Dai

Towards this end, snapshot compressive imaging (SCI) was proposed as a promising solution to improve the throughput of imaging systems by compressive sampling and computational reconstruction.

Multimodal Contrastive Training for Visual Representation Learning

no code implementations CVPR 2021 Xin Yuan, Zhe Lin, Jason Kuen, Jianming Zhang, Yilin Wang, Michael Maire, Ajinkya Kale, Baldo Faieta

We first train our model on COCO and evaluate the learned visual representations on various downstream tasks including image classification, object detection, and instance segmentation.

Cross-Modal Retrieval Image Classification +6

Universal and Flexible Optical Aberration Correction Using Deep-Prior Based Deconvolution

1 code implementation ICCV 2021 Xiu Li, Jinli Suo, Weihang Zhang, Xin Yuan, Qionghai Dai

High quality imaging usually requires bulky and expensive lenses to compensate geometric and chromatic aberrations.

Deep Gaussian Scale Mixture Prior for Spectral Compressive Imaging

1 code implementation CVPR 2021 Tao Huang, Weisheng Dong, Xin Yuan, Jinjian Wu, Guangming Shi

Different from existing GSM models using hand-crafted scale priors (e. g., the Jeffrey's prior), we propose to learn the scale prior through a deep convolutional neural network (DCNN).

Snapshot Compressive Imaging: Principle, Implementation, Theory, Algorithms and Applications

no code implementations7 Mar 2021 Xin Yuan, David J. Brady, Aggelos K. Katsaggelos

Via novel optical designs, the 2D detector samples the HD data in a {\em compressive} manner; following this, algorithms are employed to reconstruct the desired HD data-cube.

Memory-Efficient Network for Large-scale Video Compressive Sensing

2 code implementations CVPR 2021 Ziheng Cheng, Bo Chen, Guanliang Liu, Hao Zhang, Ruiying Lu, Zhengjue Wang, Xin Yuan

With the knowledge of masks, optimization algorithms or deep learning methods are employed to reconstruct the desired high-speed video frames from this snapshot measurement.

Compressive Sensing Demosaicking +1

MetaSCI: Scalable and Adaptive Reconstruction for Video Compressive Sensing

2 code implementations CVPR 2021 Zhengjue Wang, Hao Zhang, Ziheng Cheng, Bo Chen, Xin Yuan

To capture high-speed videos using a two-dimensional detector, video snapshot compressive imaging (SCI) is a promising system, where the video frames are coded by different masks and then compressed to a snapshot measurement.

Compressive Sensing Video Compressive Sensing

Plug-and-Play Algorithms for Video Snapshot Compressive Imaging

1 code implementation13 Jan 2021 Xin Yuan, Yang Liu, Jinli Suo, Frédo Durand, Qionghai Dai

On the other hand, applying SCI to large-scale problems (HD or UHD videos) in our daily life is still challenging and one of the bottlenecks lies in the reconstruction algorithm.

Demosaicking Denoising

Fast Hyperspectral Image Recovery via Non-iterative Fusion of Dual-Camera Compressive Hyperspectral Imaging

no code implementations30 Dec 2020 wei he, Naoto Yokoya, Xin Yuan

Specifically, the RGB measurement is utilized to estimate the coefficients, meanwhile the CASSI measurement is adopted to provide the orthogonal spectral basis.

GAP-net for Snapshot Compressive Imaging

1 code implementation13 Dec 2020 Ziyi Meng, Shirin Jalali, Xin Yuan

The hardware encoder typically consists of an (optical) imaging system designed to capture {compressed measurements}.

Multi-Path Routing on the Jellyfish Networks

no code implementations3 Dec 2020 Zaid ALzaid, Xin Yuan, Saptarshi Bhowmik

The Jellyfish network has recently be proposed as an alternate to the fat-tree network as the interconnect for data centers and high performance computing clusters.

Networking and Internet Architecture Distributed, Parallel, and Cluster Computing

Re-identification = Retrieval + Verification: Back to Essence and Forward with a New Metric

1 code implementation23 Nov 2020 Zheng Wang, Xin Yuan, Toshihiko Yamasaki, Yutian Lin, Xin Xu, Wenjun Zeng

In essence, current re-ID overemphasizes the importance of retrieval but underemphasizes that of verification, \textit{i. e.}, all returned images are considered as the target.

Image Retrieval Retrieval

Performance Evaluation and Modeling of Cryptographic Libraries for MPI Communications

1 code implementation13 Oct 2020 Abu Naser, Mehran Sadeghi Lahijani, Cong Wu, Mohsen Gavahi, Viet Tung Hoang, Zhi Wang, Xin Yuan

In order for High-Performance Computing (HPC) applications with data security requirements to execute in the public cloud, the cloud infrastructure must ensure the privacy and integrity of data.

Distributed, Parallel, and Cluster Computing Cryptography and Security

CryptMPI: A Fast Encrypted MPI Library

1 code implementation13 Oct 2020 Abu Naser, Cong Wu, Mehran Sadeghi Lahijani, Mohsen Gavahi, Viet Tung Hoang, Zhi Wang, Xin Yuan

The cloud infrastructure must provide security for High-Performance Computing (HPC) applications of sensitive data to execute in such an environment.

Distributed, Parallel, and Cluster Computing Cryptography and Security

Spatial--spectral FFPNet: Attention-Based Pyramid Network for Segmentation and Classification of Remote Sensing Images

no code implementations20 Aug 2020 Qingsong Xu, Xin Yuan, Chaojun Ouyang, Yue Zeng

First, a novel segmentation framework, called the heavy-weight spatial feature fusion pyramid network (FFPNet), is proposed to address the spatial problem of high-resolution remote sensing images.

Classification General Classification +2

Growing Efficient Deep Networks by Structured Continuous Sparsification

no code implementations ICLR 2021 Xin Yuan, Pedro Savarese, Michael Maire

We develop an approach to growing deep network architectures over the course of training, driven by a principled combination of accuracy and sparsity objectives.

Image Classification Language Modelling +1

The Power of Triply Complementary Priors for Image Compressive Sensing

no code implementations16 May 2020 Zhiyuan Zha, Xin Yuan, Joey Tianyi Zhou, Jiantao Zhou, Bihan Wen, Ce Zhu

In this paper, we propose a joint low-rank and deep (LRD) image model, which contains a pair of triply complementary priors, namely \textit{external} and \textit{internal}, \textit{deep} and \textit{shallow}, and \textit{local} and \textit{non-local} priors.

Compressive Sensing Image Restoration

Various Total Variation for Snapshot Video Compressive Imaging

no code implementations16 May 2020 Xin Yuan

Various TV denoising and projection algorithms are developed and tested for video SCI reconstruction on both simulation and real datasets.


Plug-and-Play Algorithms for Large-scale Snapshot Compressive Imaging

3 code implementations CVPR 2020 Xin Yuan, Yang Liu, Jinli Suo, Qionghai Dai

Snapshot compressive imaging (SCI) aims to capture the high-dimensional (usually 3D) images using a 2D sensor (detector) in a single snapshot.


ADCC: An Effective and Intelligent Attention Dense Color Constancy System for Studying Images in Smart Cities

no code implementations17 Nov 2019 Yilang Zhang, Neal N. Xiong, Zheng Wei, Xin Yuan, Jian Wang

The augmented images help to tell apart the edge gradients, edge pixels and non-edge ones in log-histogram, which contribute significantly to the feature extraction and color-ambiguity elimination, thereby advancing the accuracy of illuminant estimation.

Color Constancy

DRCAS: Deep Restoration Network for Hardware Based Compressive Acquisition Scheme

no code implementations23 Sep 2019 Pravir Singh Gupta, Xin Yuan, Gwan Seong Choi

Bearing these concerns in mind, we propose DRCAS (Deep Restoration network for hardware based Compressed Acquisition Scheme), which to our best knowledge, is the first work proposed in the literature for restoration of images acquired using acquisition scheme like HCAS.

Image Restoration Image Super-Resolution

Auto-encoders for compressed sensing

no code implementations NeurIPS Workshop Deep_Invers 2019 Pei Peng, Shirin Jalali, Xin Yuan

Compressed sensing is about recovering a structured high-dimensional signal ${\bf x}\in R^n$ from its under-determined noisy linear measurements ${\bf y}\in R^m$, where $m\ll n$.

Enhanced Bayesian Compression via Deep Reinforcement Learning

no code implementations CVPR 2019 Xin Yuan, Liangliang Ren, Jiwen Lu, Jie Zhou

In this paper, we propose an Enhanced Bayesian Compression method to flexibly compress the deep networks via reinforcement learning.

Quantization reinforcement-learning +1

Deep Reinforcement Learning with Iterative Shift for Visual Tracking

no code implementations ECCV 2018 Liangliang Ren, Xin Yuan, Jiwen Lu, Ming Yang, Jie Zhou

Visual tracking is confronted by the dilemma to locate a target both}accurately and efficiently, and make decisions online whether and how to adapt the appearance model or even restart tracking.

Motion Estimation Object +4

Relaxation-Free Deep Hashing via Policy Gradient

no code implementations ECCV 2018 Xin Yuan, Liangliang Ren, Jiwen Lu, Jie zhou

In this paper, we propose a simple yet effective relaxation-free method to learn more effective binary codes via policy gradient for scalable image search.

Deep Hashing Image Retrieval

Rank Minimization for Snapshot Compressive Imaging

3 code implementations20 Jul 2018 Yang Liu, Xin Yuan, Jinli Suo, David J. Brady, Qionghai Dai

We further investigate the special structure of the sampling process in SCI to tackle the computational workload and memory issues in SCI reconstruction.

From Rank Estimation to Rank Approximation: Rank Residual Constraint for Image Restoration

1 code implementation6 Jul 2018 Zhiyuan Zha, Xin Yuan, Bihan Wen, Jiantao Zhou, Jiachao Zhang, Ce Zhu

Towards this end, we first obtain a good reference of the original image groups by using the image NSS prior, and then the rank residual of the image groups between this reference and the degraded image is minimized to achieve a better estimate to the desired image.

Image Compression Image Denoising +1

Deep Hashing via Discrepancy Minimization

no code implementations CVPR 2018 Zhixiang Chen, Xin Yuan, Jiwen Lu, Qi Tian, Jie zhou

This paper presents a discrepancy minimizing model to address the discrete optimization problem in hashing learning.

Deep Hashing

Group Sparsity Residual with Non-Local Samples for Image Denoising

no code implementations22 Mar 2018 Zhiyuan Zha, Xinggan Zhang, Qiong Wang, Yechao Bai, Lan Tang, Xin Yuan

Inspired by group-based sparse coding, recently proposed group sparsity residual (GSR) scheme has demonstrated superior performance in image processing.

Image Denoising

Block-wise Lensless Compressive Camera

no code implementations19 Jan 2017 Xin Yuan, Gang Huang, Hong Jiang, Paul Wilford

2) The coding patterns used in each block can be the same, therefore the sensing matrix is only of the block size compared to the entire image size in existing $\text{L}^2\text{C}^2$.

Compressive Sensing Image Reconstruction

Compressive Sensing via Convolutional Factor Analysis

no code implementations11 Jan 2017 Xin Yuan, Yunchen Pu, Lawrence Carin

During reconstruction and testing, we project the upper layer dictionary to the data level and only a single layer deconvolution is required.

Compressive Sensing General Classification

A Deep Generative Deconvolutional Image Model

no code implementations23 Dec 2015 Yunchen Pu, Xin Yuan, Andrew Stevens, Chunyuan Li, Lawrence Carin

A deep generative model is developed for representation and analysis of images, based on a hierarchical convolutional dictionary-learning framework.

Dictionary Learning Image Generation

Compressive Sensing via Low-Rank Gaussian Mixture Models

no code implementations27 Aug 2015 Xin Yuan, Hong Jiang, Gang Huang, Paul A. Wilford

We develop a new compressive sensing (CS) inversion algorithm by utilizing the Gaussian mixture model (GMM).

Compressive Sensing

Lensless Compressive Imaging

no code implementations14 Aug 2015 Xin Yuan, Hong Jiang, Gang Huang, Paul Wilford

We develop a lensless compressive imaging architecture, which consists of an aperture assembly and a single sensor, without using any lens.

A Generative Model for Deep Convolutional Learning

no code implementations15 Apr 2015 Yunchen Pu, Xin Yuan, Lawrence Carin

A generative model is developed for deep (multi-layered) convolutional dictionary learning.

Dictionary Learning General Classification

Compressive Hyperspectral Imaging with Side Information

no code implementations22 Feb 2015 Xin Yuan, Tsung-Han Tsai, Ruoyu Zhu, Patrick Llull, David Brady, Lawrence Carin

By using RGB images as side information of the compressive sensing system, the proposed approach is extended to learn a coupled dictionary from the joint dataset of the compressed measurements and the corresponding RGB images, to improve reconstruction quality.

Compressive Sensing

Generative Deep Deconvolutional Learning

no code implementations18 Dec 2014 Yunchen Pu, Xin Yuan, Lawrence Carin

A generative Bayesian model is developed for deep (multi-layer) convolutional dictionary learning.

Dictionary Learning General Classification

Bayesian Nonlinear Support Vector Machines and Discriminative Factor Modeling

no code implementations NeurIPS 2014 Ricardo Henao, Xin Yuan, Lawrence Carin

A new Bayesian formulation is developed for nonlinear support vector machines (SVMs), based on a Gaussian process and with the SVM hinge loss expressed as a scaled mixture of normals.

Classification and Reconstruction of High-Dimensional Signals from Low-Dimensional Features in the Presence of Side Information

no code implementations1 Dec 2014 Francesco Renna, Liming Wang, Xin Yuan, Jianbo Yang, Galen Reeves, Robert Calderbank, Lawrence Carin, Miguel R. D. Rodrigues

These conditions, which are reminiscent of the well-known Slepian-Wolf and Wyner-Ziv conditions, are a function of the number of linear features extracted from the signal of interest, the number of linear features extracted from the side information signal, and the geometry of these signals and their interplay.

General Classification

Tree-Structure Bayesian Compressive Sensing for Video

no code implementations12 Oct 2014 Xin Yuan, Patrick Llull, David J. Brady, Lawrence Carin

A Bayesian compressive sensing framework is developed for video reconstruction based on the color coded aperture compressive temporal imaging (CACTI) system.

Compressive Sensing Video Reconstruction

Low-Cost Compressive Sensing for Color Video and Depth

no code implementations CVPR 2014 Xin Yuan, Patrick Llull, Xuejun Liao, Jianbo Yang, Guillermo Sapiro, David J. Brady, Lawrence Carin

A simple and inexpensive (low-power and low-bandwidth) modification is made to a conventional off-the-shelf color video camera, from which we recover {multiple} color frames for each of the original measured frames, and each of the recovered frames can be focused at a different depth.

Compressive Sensing Translation

Multiscale Shrinkage and Lévy Processes

no code implementations11 Jan 2014 Xin Yuan, Vinayak Rao, Shaobo Han, Lawrence Carin

The method we consider in detail, and for which numerical results are presented, is based on increments of a gamma process.

Bayesian Inference Compressive Sensing +1

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