Search Results for author: Chunle Guo

Found 20 papers, 12 papers with code

The Ninth NTIRE 2024 Efficient Super-Resolution Challenge Report

1 code implementation16 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

LAMP: Learn A Motion Pattern for Few-Shot-Based Video Generation

1 code implementation16 Oct 2023 Ruiqi Wu, Liangyu Chen, Tong Yang, Chunle Guo, Chongyi Li, Xiangyu Zhang

Specifically, we design a first-frame-conditioned pipeline that uses an off-the-shelf text-to-image model for content generation so that our tuned video diffusion model mainly focuses on motion learning.

Image Animation Text-to-Image Generation +2

Synergistic Multiscale Detail Refinement via Intrinsic Supervision for Underwater Image Enhancement

1 code implementation23 Aug 2023 Dehuan Zhang, Jingchun Zhou, Chunle Guo, Weishi Zhang, Chongyi Li

Therefore, we present the synergistic multi-scale detail refinement via intrinsic supervision (SMDR-IS) for enhancing underwater scene details, which contain multi-stages.

Image Enhancement Underwater Image Restoration

AMSP-UOD: When Vortex Convolution and Stochastic Perturbation Meet Underwater Object Detection

1 code implementation23 Aug 2023 Jingchun Zhou, Zongxin He, Kin-Man Lam, Yudong Wang, Weishi Zhang, Chunle Guo, Chongyi Li

In this paper, we present a novel Amplitude-Modulated Stochastic Perturbation and Vortex Convolutional Network, AMSP-UOD, designed for underwater object detection.

FAD Object +2

Make Explicit Calibration Implicit: Calibrate Denoiser Instead of the Noise Model

1 code implementation ICCV 2023 Xin Jin, Jia-Wen Xiao, Ling-Hao Han, Chunle Guo, Xialei Liu, Chongyi Li, Ming-Ming Cheng

However, these methods are impeded by several critical limitations: a) the explicit calibration process is both labor- and time-intensive, b) challenge exists in transferring denoisers across different camera models, and c) the disparity between synthetic and real noise is exacerbated by digital gain.

Image Denoising

Random Weights Networks Work as Loss Prior Constraint for Image Restoration

no code implementations29 Mar 2023 Man Zhou, Naishan Zheng, Jie Huang, Xiangyu Rui, Chunle Guo, Deyu Meng, Chongyi Li, Jinwei Gu

In this paper, orthogonal to the existing data and model studies, we instead resort our efforts to investigate the potential of loss function in a new perspective and present our belief ``Random Weights Networks can Be Acted as Loss Prior Constraint for Image Restoration''.

Image Restoration Image Super-Resolution +1

Unlocking Masked Autoencoders as Loss Function for Image and Video Restoration

no code implementations29 Mar 2023 Man Zhou, Naishan Zheng, Jie Huang, Chunle Guo, Chongyi Li

We investigate the efficacy of our belief from three perspectives: 1) from task-customized MAE to native MAE, 2) from image task to video task, and 3) from transformer structure to convolution neural network structure.

Image Denoising Image Enhancement +4

BeautyREC: Robust, Efficient, and Content-preserving Makeup Transfer

no code implementations12 Dec 2022 Qixin Yan, Chunle Guo, Jixin Zhao, Yuekun Dai, Chen Change Loy, Chongyi Li

The key insights of this study are modeling component-specific correspondence for local makeup transfer, capturing long-range dependencies for global makeup transfer, and enabling efficient makeup transfer via a single-path structure.

Underwater Ranker: Learn Which Is Better and How to Be Better

1 code implementation14 Aug 2022 Chunle Guo, Ruiqi Wu, Xin Jin, Linghao Han, Zhi Chai, Weidong Zhang, Chongyi Li

To achieve that, we also contribute a dataset, URankerSet, containing sufficient results enhanced by different UIE algorithms and the corresponding perceptual rankings, to train our URanker.

Image Quality Assessment UIE

CuDi: Curve Distillation for Efficient and Controllable Exposure Adjustment

no code implementations28 Jul 2022 Chongyi Li, Chunle Guo, Ruicheng Feng, Shangchen Zhou, Chen Change Loy

Our method inherits the zero-reference learning and curve-based framework from an effective low-light image enhancement method, Zero-DCE, with further speed up in its inference speed, reduction in its model size, and extension to controllable exposure adjustment.

Low-Light Image Enhancement

Underwater Image Enhancement via Medium Transmission-Guided Multi-Color Space Embedding

5 code implementations27 Apr 2021 Chongyi Li, Saeed Anwar, Junhui Hou, Runmin Cong, Chunle Guo, Wenqi Ren

As a result, our network can effectively improve the visual quality of underwater images by exploiting multiple color spaces embedding and the advantages of both physical model-based and learning-based methods.

Ranked #2 on Underwater Image Restoration on LSUI (using extra training data)

Image Enhancement Underwater Image Restoration

Low-Light Image and Video Enhancement Using Deep Learning: A Survey

3 code implementations21 Apr 2021 Chongyi Li, Chunle Guo, Linghao Han, Jun Jiang, Ming-Ming Cheng, Jinwei Gu, Chen Change Loy

Low-light image enhancement (LLIE) aims at improving the perception or interpretability of an image captured in an environment with poor illumination.

Face Detection Low-Light Image Enhancement +1

Learning to Enhance Low-Light Image via Zero-Reference Deep Curve Estimation

4 code implementations1 Mar 2021 Chongyi Li, Chunle Guo, Chen Change Loy

This paper presents a novel method, Zero-Reference Deep Curve Estimation (Zero-DCE), which formulates light enhancement as a task of image-specific curve estimation with a deep network.

Face Detection Image Enhancement

Flexible Piecewise Curves Estimation for Photo Enhancement

no code implementations26 Oct 2020 Chongyi Li, Chunle Guo, Qiming Ai, Shangchen Zhou, Chen Change Loy

This paper presents a new method, called FlexiCurve, for photo enhancement.

A Parallel Down-Up Fusion Network for Salient Object Detection in Optical Remote Sensing Images

no code implementations2 Oct 2020 Chongyi Li, Runmin Cong, Chunle Guo, Hua Li, Chunjie Zhang, Feng Zheng, Yao Zhao

In this paper, we propose a novel Parallel Down-up Fusion network (PDF-Net) for SOD in optical RSIs, which takes full advantage of the in-path low- and high-level features and cross-path multi-resolution features to distinguish diversely scaled salient objects and suppress the cluttered backgrounds.

object-detection Object Detection +1

Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement

9 code implementations CVPR 2020 Chunle Guo, Chongyi Li, Jichang Guo, Chen Change Loy, Junhui Hou, Sam Kwong, Runmin Cong

The paper presents a novel method, Zero-Reference Deep Curve Estimation (Zero-DCE), which formulates light enhancement as a task of image-specific curve estimation with a deep network.

Color Constancy Face Detection +1

An Underwater Image Enhancement Benchmark Dataset and Beyond

1 code implementation11 Jan 2019 Chongyi Li, Chunle Guo, Wenqi Ren, Runmin Cong, Junhui Hou, Sam Kwong, DaCheng Tao

In this paper, we construct an Underwater Image Enhancement Benchmark (UIEB) including 950 real-world underwater images, 890 of which have the corresponding reference images.

Ranked #5 on Underwater Image Restoration on LSUI (using extra training data)

Image Enhancement Underwater Image Restoration

DR-Net: Transmission Steered Single Image Dehazing Network with Weakly Supervised Refinement

no code implementations2 Dec 2017 Chongyi Li, Jichang Guo, Fatih Porikli, Chunle Guo, Huzhu Fu, Xi Li

Despite the recent progress in image dehazing, several problems remain largely unsolved such as robustness for varying scenes, the visual quality of reconstructed images, and effectiveness and flexibility for applications.

Image Dehazing Single Image Dehazing +1

Emerging from Water: Underwater Image Color Correction Based on Weakly Supervised Color Transfer

no code implementations19 Oct 2017 Chongyi Li, Jichang Guo, Chunle Guo

Underwater vision suffers from severe effects due to selective attenuation and scattering when light propagates through water.

SSIM

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