Search Results for author: Jiantao Zhou

Found 45 papers, 28 papers with code

Text-Driven Traffic Anomaly Detection with Temporal High-Frequency Modeling in Driving Videos

no code implementations7 Jan 2024 Rongqin Liang, Yuanman Li, Jiantao Zhou, Xia Li

Traffic anomaly detection (TAD) in driving videos is critical for ensuring the safety of autonomous driving and advanced driver assistance systems.

Anomaly Detection Autonomous Driving +1

Progressive Poisoned Data Isolation for Training-time Backdoor Defense

1 code implementation20 Dec 2023 Yiming Chen, Haiwei Wu, Jiantao Zhou

Extensive experiments on multiple benchmark datasets and DNN models, assessed against nine state-of-the-art backdoor attacks, demonstrate the superior performance of our PIPD method for backdoor defense.

backdoor defense Data Poisoning

Image Demoireing in RAW and sRGB Domains

no code implementations14 Dec 2023 Shuning Xu, Binbin Song, Xiangyu Chen, Xina Liu, Jiantao Zhou

Moire patterns frequently appear when capturing screens with smartphones or cameras, potentially compromising image quality.

SSIM

SmartEdit: Exploring Complex Instruction-based Image Editing with Multimodal Large Language Models

1 code implementation11 Dec 2023 Yuzhou Huang, Liangbin Xie, Xintao Wang, Ziyang Yuan, Xiaodong Cun, Yixiao Ge, Jiantao Zhou, Chao Dong, Rui Huang, Ruimao Zhang, Ying Shan

Both quantitative and qualitative results on this evaluation dataset indicate that our SmartEdit surpasses previous methods, paving the way for the practical application of complex instruction-based image editing.

Regroup Median Loss for Combating Label Noise

no code implementations11 Dec 2023 Fengpeng Li, Kemou Li, Jinyu Tian, Jiantao Zhou

The deep model training procedure requires large-scale datasets of annotated data.

Recoverable Privacy-Preserving Image Classification through Noise-like Adversarial Examples

1 code implementation19 Oct 2023 Jun Liu, Jiantao Zhou, Jinyu Tian, Weiwei Sun

Extensive experiments demonstrate that 1) the classification accuracy of the classifier trained in the plaintext domain remains the same in both the ciphertext and plaintext domains; 2) the encrypted images can be recovered into their original form with an average PSNR of up to 51+ dB for the SVHN dataset and 48+ dB for the VGGFace2 dataset; 3) our system exhibits satisfactory generalization capability on the encryption, decryption and classification tasks across datasets that are different from the training one; and 4) a high-level of security is achieved against three potential threat models.

Cloud Computing Image Classification +1

Generating Robust Adversarial Examples against Online Social Networks (OSNs)

1 code implementation19 Oct 2023 Jun Liu, Jiantao Zhou, Haiwei Wu, Weiwei Sun, Jinyu Tian

In this work, we aim to design a new framework for generating robust AEs that can survive the OSN transmission; namely, the AEs before and after the OSN transmission both possess strong attack capabilities.

A Comparative Study of Image Restoration Networks for General Backbone Network Design

1 code implementation18 Oct 2023 Xiangyu Chen, Zheyuan Li, Yuandong Pu, Yihao Liu, Jiantao Zhou, Yu Qiao, Chao Dong

Following this, we present the benchmark results and analyze the reasons behind the performance disparity of different models across various tasks.

Image Restoration

Unifying Image Processing as Visual Prompting Question Answering

no code implementations16 Oct 2023 Yihao Liu, Xiangyu Chen, Xianzheng Ma, Xintao Wang, Jiantao Zhou, Yu Qiao, Chao Dong

To address this issue, we propose a universal model for general image processing that covers image restoration, image enhancement, image feature extraction tasks, etc.

Image Enhancement Image Restoration +4

HAT: Hybrid Attention Transformer for Image Restoration

2 code implementations11 Sep 2023 Xiangyu Chen, Xintao Wang, Wenlong Zhang, Xiangtao Kong, Yu Qiao, Jiantao Zhou, Chao Dong

In the training stage, we additionally adopt a same-task pre-training strategy to further exploit the potential of the model for further improvement.

Image Compression Image Denoising +2

CNN Injected Transformer for Image Exposure Correction

1 code implementation8 Sep 2023 Shuning Xu, Xiangyu Chen, Binbin Song, Jiantao Zhou

Capturing images with incorrect exposure settings fails to deliver a satisfactory visual experience.

Blocking

Direction-aware Video Demoireing with Temporal-guided Bilateral Learning

1 code implementation25 Aug 2023 Shuning Xu, Binbin Song, Xiangyu Chen, Jiantao Zhou

In TDR, we propose a temporal-guided bilateral learning pipeline to mitigate the degradation of color and details caused by the moire patterns while preserving the restored frequency information in FDDA.

Rethinking Image Forgery Detection via Contrastive Learning and Unsupervised Clustering

1 code implementation18 Aug 2023 Haiwei Wu, Yiming Chen, Jiantao Zhou

To resolve this dilemma, we propose the FOrensic ContrAstive cLustering (FOCAL) method, a novel, simple yet very effective paradigm based on contrastive learning and unsupervised clustering for the image forgery detection.

Clustering Contrastive Learning +1

Under-Display Camera Image Restoration with Scattering Effect

1 code implementation ICCV 2023 Binbin Song, Xiangyu Chen, Shuning Xu, Jiantao Zhou

With the physical model of the scattering effect, we improve the image formation pipeline for the image synthesis to construct a realistic UDC dataset with ground truths.

Image Generation Image Restoration

A Memory-Augmented Multi-Task Collaborative Framework for Unsupervised Traffic Accident Detection in Driving Videos

no code implementations27 Jul 2023 Rongqin Liang, Yuanman Li, Yingxin Yi, Jiantao Zhou, Xia Li

Different from previous approaches, our method can more accurately detect both ego-involved and non-ego accidents by simultaneously modeling appearance changes and object motions in video frames through the collaboration of optical flow reconstruction and future object localization tasks.

Autonomous Driving Object +3

DeSRA: Detect and Delete the Artifacts of GAN-based Real-World Super-Resolution Models

1 code implementation5 Jul 2023 Liangbin Xie, Xintao Wang, Xiangyu Chen, Gen Li, Ying Shan, Jiantao Zhou, Chao Dong

After detecting the artifact regions, we develop a finetune procedure to improve GAN-based SR models with a few samples, so that they can deal with similar types of artifacts in more unseen real data.

Image Super-Resolution

Common Knowledge Learning for Generating Transferable Adversarial Examples

no code implementations1 Jul 2023 Ruijie Yang, Yuanfang Guo, Junfu Wang, Jiantao Zhou, Yunhong Wang

Specifically, to reduce the model-specific features and obtain better output distributions, we construct a multi-teacher framework, where the knowledge is distilled from different teacher architectures into one student network.

Generalizable Synthetic Image Detection via Language-guided Contrastive Learning

1 code implementation23 May 2023 Haiwei Wu, Jiantao Zhou, Shile Zhang

In this work, we propose a simple yet very effective synthetic image detection method via a language-guided contrastive learning and a new formulation of the detection problem.

Contrastive Learning Image Generation +1

STGlow: A Flow-based Generative Framework with Dual Graphormer for Pedestrian Trajectory Prediction

no code implementations21 Nov 2022 Rongqin Liang, Yuanman Li, Jiantao Zhou, Xia Li

Different from previous approaches, our method can more precisely model the underlying data distribution by optimizing the exact log-likelihood of motion behaviors.

Anomaly Detection Autonomous Driving +3

Cross-receptive Focused Inference Network for Lightweight Image Super-Resolution

1 code implementation6 Jul 2022 Wenjie Li, Juncheng Li, Guangwei Gao, Jiantao Zhou, Jian Yang, Guo-Jun Qi

Recently, Transformer-based methods have shown impressive performance in single image super-resolution (SISR) tasks due to the ability of global feature extraction.

Image Super-Resolution

Deep Posterior Distribution-based Embedding for Hyperspectral Image Super-resolution

1 code implementation30 May 2022 Jinhui Hou, Zhiyu Zhu, Junhui Hou, Huanqiang Zeng, Jinjian Wu, Jiantao Zhou

Then, we incorporate the proposed feature embedding scheme into a source-consistent super-resolution framework that is physically-interpretable, producing lightweight PDE-Net, in which high-resolution (HR) HS images are iteratively refined from the residuals between input low-resolution (LR) HS images and pseudo-LR-HS images degenerated from reconstructed HR-HS images via probability-inspired HS embedding.

Hyperspectral Image Super-Resolution Image Super-Resolution

NTIRE 2022 Challenge on High Dynamic Range Imaging: Methods and Results

no code implementations25 May 2022 Eduardo Pérez-Pellitero, Sibi Catley-Chandar, Richard Shaw, Aleš Leonardis, Radu Timofte, Zexin Zhang, Cen Liu, Yunbo Peng, Yue Lin, Gaocheng Yu, Jin Zhang, Zhe Ma, Hongbin Wang, Xiangyu Chen, Xintao Wang, Haiwei Wu, Lin Liu, Chao Dong, Jiantao Zhou, Qingsen Yan, Song Zhang, Weiye Chen, Yuhang Liu, Zhen Zhang, Yanning Zhang, Javen Qinfeng Shi, Dong Gong, Dan Zhu, Mengdi Sun, Guannan Chen, Yang Hu, Haowei Li, Baozhu Zou, Zhen Liu, Wenjie Lin, Ting Jiang, Chengzhi Jiang, Xinpeng Li, Mingyan Han, Haoqiang Fan, Jian Sun, Shuaicheng Liu, Juan Marín-Vega, Michael Sloth, Peter Schneider-Kamp, Richard Röttger, Chunyang Li, Long Bao, Gang He, Ziyao Xu, Li Xu, Gen Zhan, Ming Sun, Xing Wen, Junlin Li, Shuang Feng, Fei Lei, Rui Liu, Junxiang Ruan, Tianhong Dai, Wei Li, Zhan Lu, Hengyan Liu, Peian Huang, Guangyu Ren, Yonglin Luo, Chang Liu, Qiang Tu, Fangya Li, Ruipeng Gang, Chenghua Li, Jinjing Li, Sai Ma, Chenming Liu, Yizhen Cao, Steven Tel, Barthelemy Heyrman, Dominique Ginhac, Chul Lee, Gahyeon Kim, Seonghyun Park, An Gia Vien, Truong Thanh Nhat Mai, Howoon Yoon, Tu Vo, Alexander Holston, Sheir Zaheer, Chan Y. Park

The challenge is composed of two tracks with an emphasis on fidelity and complexity constraints: In Track 1, participants are asked to optimize objective fidelity scores while imposing a low-complexity constraint (i. e. solutions can not exceed a given number of operations).

Image Restoration Vocal Bursts Intensity Prediction

Activating More Pixels in Image Super-Resolution Transformer

2 code implementations CVPR 2023 Xiangyu Chen, Xintao Wang, Jiantao Zhou, Yu Qiao, Chao Dong

In the training stage, we additionally adopt a same-task pre-training strategy to exploit the potential of the model for further improvement.

Image Super-Resolution

Tag-assisted Multimodal Sentiment Analysis under Uncertain Missing Modalities

1 code implementation28 Apr 2022 Jiandian Zeng, Tianyi Liu, Jiantao Zhou

Specifically, we design a tag encoding module to cover both the single modality and multiple modalities missing cases, so as to guide the network's attention to those missing modalities.

Multimodal Sentiment Analysis Sentiment Classification +1

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

A Principled Design of Image Representation: Towards Forensic Tasks

1 code implementation2 Mar 2022 Shuren Qi, Yushu Zhang, Chao Wang, Jiantao Zhou, Xiaochun Cao

Image forensics is a rising topic as the trustworthy multimedia content is critical for modern society.

Image Forensics

Probabilistic Selective Encryption of Convolutional Neural Networks for Hierarchical Services

no code implementations CVPR 2021 Jinyu Tian, Jiantao Zhou, Jia Duan

Model protection is vital when deploying Convolutional Neural Networks (CNNs) for commercial services, due to the massive costs of training them.

Denoising

Self-Supervised Adversarial Example Detection by Disentangled Representation

no code implementations NeurIPS 2021 Zhaoxi Zhang, Leo Yu Zhang, Xufei Zheng, Jinyu Tian, Jiantao Zhou

To alleviate this problem, we explore how to detect adversarial examples with disentangled label/semantic features under the autoencoder structure.

Adversarial Attack

Detecting Adversarial Examples from Sensitivity Inconsistency of Spatial-Transform Domain

1 code implementation7 Mar 2021 Jinyu Tian, Jiantao Zhou, Yuanman Li, Jia Duan

Deep neural networks (DNNs) have been shown to be vulnerable against adversarial examples (AEs), which are maliciously designed to cause dramatic model output errors.

GIID-Net: Generalizable Image Inpainting Detection via Neural Architecture Search and Attention

1 code implementation19 Jan 2021 Haiwei Wu, Jiantao Zhou

The proposed GIID-Net consists of three sub-blocks: the enhancement block, the extraction block and the decision block.

Image Inpainting Neural Architecture Search

Temporal Pyramid Network for Pedestrian Trajectory Prediction with Multi-Supervision

1 code implementation3 Dec 2020 Rongqin Liang, Yuanman Li, Xia Li, Yi Tang, Jiantao Zhou, Wenbin Zou

Predicting human motion behavior in a crowd is important for many applications, ranging from the natural navigation of autonomous vehicles to intelligent security systems of video surveillance.

Autonomous Vehicles Pedestrian Trajectory Prediction +1

SMDS-Net: Model Guided Spectral-Spatial Network for Hyperspectral Image Denoising

no code implementations3 Dec 2020 Fengchao Xiong, Shuyin Tao, Jun Zhou, Jianfeng Lu, Jiantao Zhou, Yuntao Qian

This model first projects the observed HSIs into a low-dimensional orthogonal subspace, and then represents the projected image with a multidimensional dictionary.

Hyperspectral Image Denoising Image Denoising

Deep Generative Model for Image Inpainting with Local Binary Pattern Learning and Spatial Attention

1 code implementation2 Sep 2020 Haiwei Wu, Jiantao Zhou, Yuanman Li

Deep learning (DL) has demonstrated its powerful capabilities in the field of image inpainting.

Image Inpainting

Privacy Leakage of SIFT Features via Deep Generative Model based Image Reconstruction

1 code implementation2 Sep 2020 Haiwei Wu, Jiantao Zhou

It is shown that, if the adversary can only have access to the SIFT descriptors while not their coordinates, then the modest success of reconstructing the latent image can be achieved for highly-structured images (e. g., faces) and would fail in general settings.

Content-Based Image Retrieval Image Reconstruction +2

Hyperspectral Image Super-resolution via Deep Progressive Zero-centric Residual Learning

1 code implementation18 Jun 2020 Zhiyu Zhu, Junhui Hou, Jie Chen, Huanqiang Zeng, Jiantao Zhou

Specifically, PZRes-Net learns a high resolution and \textit{zero-centric} residual image, which contains high-frequency spatial details of the scene across all spectral bands, from both inputs in a progressive fashion along the spectral dimension.

Hyperspectral Image Super-Resolution Hyperspectral Unmixing +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

Toward Better Understanding of Saliency Prediction in Augmented 360 Degree Videos

no code implementations12 Dec 2019 Yucheng Zhu, Xiongkuo Min, Dandan Zhu, Ke Gu, Jiantao Zhou, Guangtao Zhai, Xiaokang Yang, Wenjun Zhang

The saliency annotations of head and eye movements for both original and augmented videos are collected and together constitute the ARVR dataset.

Object Recognition Optical Flow Estimation +1

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

A Comparative Study for the Nuclear Norms Minimization Methods

no code implementations16 Aug 2016 Zhiyuan Zha, Bihan Wen, Jiachao Zhang, Jiantao Zhou, Ce Zhu

Inspired by enhancing sparsity of the weighted L1-norm minimization in comparison with L1-norm minimization in sparse representation, we thus explain that WNNM is more effective than NMM.

Deblurring Dictionary Learning +2

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