Search Results for author: Jiangxin Dong

Found 25 papers, 11 papers with code

Physics-based Feature Dehazing Networks

no code implementations ECCV 2020 Jiangxin Dong, Jinshan Pan

We propose an effective feature dehazing unit (FDU), which is applied to the deep feature space to explore useful features for image dehazing based on the physics model.

Decoder Image Dehazing +1

ExpRDiff: Short-exposure Guided Diffusion Model for Realistic Local Motion Deblurring

no code implementations12 Dec 2024 Zhongbao Yang, Jiangxin Dong, Jinhui Tang, Jinshan Pan

Furthermore, to restore images realistically and visually-pleasant, we develop a short-exposure guided diffusion model that explores useful features from short-exposure images and blurred regions to better constrain the diffusion process.

Deblurring Image Restoration

FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration

no code implementations2 Dec 2024 Hao Li, Xiang Chen, Jiangxin Dong, Jinhui Tang, Jinshan Pan

Despite the significant progress made by all-in-one models in universal image restoration, existing methods suffer from a generalization bottleneck in real-world scenarios, as they are mostly trained on small-scale synthetic datasets with limited degradations.

Image Restoration Incremental Learning

FaithDiff: Unleashing Diffusion Priors for Faithful Image Super-resolution

no code implementations27 Nov 2024 Junyang Chen, Jinshan Pan, Jiangxin Dong

Faithful image super-resolution (SR) not only needs to recover images that appear realistic, similar to image generation tasks, but also requires that the restored images maintain fidelity and structural consistency with the input.

Image Generation Image Super-Resolution

Cascaded Temporal Updating Network for Efficient Video Super-Resolution

no code implementations26 Aug 2024 Hao Li, Jiangxin Dong, Jinshan Pan

However, the key components in recurrent-based VSR networks significantly impact model efficiency, e. g., the alignment module occupies a substantial portion of model parameters, while the bidirectional propagation mechanism significantly amplifies the inference time.

Video Reconstruction Video Super-Resolution

Efficient Visual State Space Model for Image Deblurring

1 code implementation23 May 2024 Lingshun Kong, Jiangxin Dong, Ming-Hsuan Yang, Jinshan Pan

Convolutional neural networks (CNNs) and Vision Transformers (ViTs) have achieved excellent performance in image restoration.

Deblurring Image Deblurring +3

The Ninth NTIRE 2024 Efficient Super-Resolution Challenge Report

3 code implementations16 Apr 2024 Bin Ren, Nancy Mehta, Radu Timofte, Hongyuan Yu, Cheng Wan, Yuxin Hong, Bingnan Han, Zhuoyuan Wu, Yajun Zou, Yuqing Liu, Jizhe Li, Keji He, Chao Fan, Heng Zhang, Xiaolin Zhang, Xuanwu Yin, Kunlong Zuo, Bohao Liao, Peizhe Xia, Long Peng, Zhibo Du, Xin Di, Wangkai Li, Yang Wang, Wei Zhai, Renjing Pei, Jiaming Guo, Songcen Xu, Yang Cao, ZhengJun Zha, Yan Wang, Yi Liu, Qing Wang, Gang Zhang, Liou Zhang, Shijie Zhao, Long Sun, Jinshan Pan, Jiangxin Dong, Jinhui Tang, Xin Liu, Min Yan, Menghan Zhou, Yiqiang Yan, Yixuan Liu, Wensong Chan, Dehua Tang, Dong Zhou, Li Wang, Lu Tian, Barsoum Emad, Bohan Jia, Junbo Qiao, Yunshuai Zhou, Yun Zhang, Wei Li, Shaohui Lin, Shenglong Zhou, Binbin Chen, Jincheng Liao, Suiyi Zhao, Zhao Zhang, Bo wang, Yan Luo, Yanyan Wei, Feng Li, Mingshen Wang, Yawei Li, Jinhan Guan, Dehua Hu, Jiawei Yu, Qisheng Xu, Tao Sun, Long Lan, Kele Xu, Xin Lin, Jingtong Yue, Lehan Yang, Shiyi Du, Lu Qi, Chao Ren, Zeyu Han, YuHan Wang, Chaolin Chen, Haobo Li, Mingjun Zheng, Zhongbao Yang, Lianhong Song, Xingzhuo Yan, Minghan Fu, Jingyi Zhang, Baiang Li, Qi Zhu, Xiaogang Xu, Dan Guo, Chunle Guo, Jiadi Chen, Huanhuan Long, Chunjiang Duanmu, Xiaoyan Lei, Jie Liu, Weilin Jia, Weifeng Cao, Wenlong Zhang, Yanyu Mao, Ruilong Guo, Nihao Zhang, Qian Wang, Manoj Pandey, Maksym Chernozhukov, Giang Le, Shuli Cheng, Hongyuan Wang, Ziyan Wei, Qingting Tang, Liejun Wang, Yongming Li, Yanhui Guo, Hao Xu, Akram Khatami-Rizi, Ahmad Mahmoudi-Aznaveh, Chih-Chung Hsu, Chia-Ming Lee, Yi-Shiuan Chou, Amogh Joshi, Nikhil Akalwadi, Sampada Malagi, Palani Yashaswini, Chaitra Desai, Ramesh Ashok Tabib, Ujwala Patil, Uma Mudenagudi

In sub-track 1, the practical runtime performance of the submissions was evaluated, and the corresponding score was used to determine the ranking.

Image Super-Resolution

ColorMNet: A Memory-based Deep Spatial-Temporal Feature Propagation Network for Video Colorization

1 code implementation9 Apr 2024 Yixin Yang, Jiangxin Dong, Jinhui Tang, Jinshan Pan

To explore this property for better spatial and temporal feature utilization, we develop a local attention module to aggregate the features from adjacent frames in a spatial-temporal neighborhood.

Colorization

Collaborative Feedback Discriminative Propagation for Video Super-Resolution

1 code implementation6 Apr 2024 Hao Li, Xiang Chen, Jiangxin Dong, Jinhui Tang, Jinshan Pan

However, inaccurate alignment usually leads to aligned features with significant artifacts, which will be accumulated during propagation and thus affect video restoration.

Video Reconstruction Video Restoration +1

Bidirectional Multi-Scale Implicit Neural Representations for Image Deraining

1 code implementation CVPR 2024 Xiang Chen, Jinshan Pan, Jiangxin Dong

To better explore the common degradation representations from spatially-varying rain streaks, we incorporate intra-scale implicit neural representations based on pixel coordinates with the degraded inputs in a closed-loop design, enabling the learned features to facilitate rain removal and improve the robustness of the model in complex scenarios.

Image Reconstruction Rain Removal

Towards Unified Deep Image Deraining: A Survey and A New Benchmark

no code implementations5 Oct 2023 Xiang Chen, Jinshan Pan, Jiangxin Dong, Jinhui Tang

In this paper, we provide a comprehensive review of existing image deraining method and provide a unify evaluation setting to evaluate the performance of image deraining methods.

Rain Removal

SelfPromer: Self-Prompt Dehazing Transformers with Depth-Consistency

1 code implementation13 Mar 2023 Cong Wang, Jinshan Pan, WanYu Lin, Jiangxin Dong, Xiao-Ming Wu

For this purpose, we develop a prompt based on the features of depth differences between the hazy input images and corresponding clear counterparts that can guide dehazing models for better restoration.

Image Dehazing Image Generation

Spatially-Adaptive Feature Modulation for Efficient Image Super-Resolution

1 code implementation ICCV 2023 Long Sun, Jiangxin Dong, Jinhui Tang, Jinshan Pan

Although numerous solutions have been proposed for image super-resolution, they are usually incompatible with low-power devices with many computational and memory constraints.

Image Super-Resolution

Multi-Scale Residual Low-Pass Filter Network for Image Deblurring

no code implementations ICCV 2023 Jiangxin Dong, Jinshan Pan, Zhongbao Yang, Jinhui Tang

We present a simple and effective Multi-scale Residual Low-Pass Filter Network (MRLPFNet) that jointly explores the image details and main structures for image deblurring.

Deblurring Decoder +1

Deep Discriminative Spatial and Temporal Network for Efficient Video Deblurring

1 code implementation CVPR 2023 Jinshan Pan, Boming Xu, Jiangxin Dong, Jianjun Ge, Jinhui Tang

In contrast to existing methods that directly align adjacent frames without discrimination, we develop a deep discriminative spatial and temporal network to facilitate the spatial and temporal feature exploration for better video deblurring.

Deblurring Video Deblurring

Efficient Frequency Domain-based Transformers for High-Quality Image Deblurring

1 code implementation CVPR 2023 Lingshun Kong, Jiangxin Dong, Mingqiang Li, Jianjun Ge, Jinshan Pan

We present an effective and efficient method that explores the properties of Transformers in the frequency domain for high-quality image deblurring.

Ranked #2 on Image Deblurring on GoPro (using extra training data)

Deblurring Decoder +3

Learning Spatially-Variant MAP Models for Non-Blind Image Deblurring

no code implementations CVPR 2021 Jiangxin Dong, Stefan Roth, Bernt Schiele

The classical maximum a-posteriori (MAP) framework for non-blind image deblurring requires defining suitable data and regularization terms, whose interplay yields the desired clear image through optimization.

Image Deblurring

DWDN: Deep Wiener Deconvolution Network for Non-Blind Image Deblurring

1 code implementation NeurIPS 2020 Jiangxin Dong, Stefan Roth, Bernt Schiele

We present a simple and effective approach for non-blind image deblurring, combining classical techniques and deep learning.

Image Deblurring

Learning Data Terms for Non-blind Deblurring

no code implementations ECCV 2018 Jiangxin Dong, Jinshan Pan, Deqing Sun, Zhixun Su, Ming-Hsuan Yang

We propose a simple and effective discriminative framework to learn data terms that can adaptively handle blurred images in the presence of severe noise and outliers.

Deblurring

Physics-Based Generative Adversarial Models for Image Restoration and Beyond

no code implementations2 Aug 2018 Jinshan Pan, Jiangxin Dong, Yang Liu, Jiawei Zhang, Jimmy Ren, Jinhui Tang, Yu-Wing Tai, Ming-Hsuan Yang

We present an algorithm to directly solve numerous image restoration problems (e. g., image deblurring, image dehazing, image deraining, etc.).

Deblurring Image Deblurring +3

Blind Image Deblurring With Outlier Handling

no code implementations ICCV 2017 Jiangxin Dong, Jinshan Pan, Zhixun Su, Ming-Hsuan Yang

We analyze the relationship between the proposed algorithm and other blind deblurring methods with outlier handling and show how to estimate intermediate latent images for blur kernel estimation principally.

Image Deblurring Outlier Detection

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