262 citations · 1.7k across the 63 of their papers we have counts for
14 papers · 1 filter
Correcting Diffusion-Based Perceptual Image Compression with Privileged End-to-End Decoder
Yiyang Ma, Wenhan Yang, Jiaying Liu
The images produced by diffusion models can attain excellent perceptual quality. However, it is challenging for diffusion models to guarantee distortion, hence the integration of d…
Diffusion Enhancement for Cloud Removal in Ultra-Resolution Remote Sensing Imagery
Jialu Sui, Yiyang Ma, Wenhan Yang +3
The presence of cloud layers severely compromises the quality and effectiveness of optical remote sensing (RS) images. However, existing deep-learning (DL)-based Cloud Removal (CR)…
Solving Diffusion ODEs with Optimal Boundary Conditions for Better Image Super-Resolution
Yiyang Ma, Huan Yang, Wenhan Yang +2
Diffusion models, as a kind of powerful generative model, have given impressive results on image super-resolution (SR) tasks. However, due to the randomness introduced in the rever…
Neural Data-Dependent Transform for Learned Image Compression
Dezhao Wang, Wenhan Yang, Yueyu Hu +1
Learned image compression has achieved great success due to its excellent modeling capacity, but seldom further considers the Rate-Distortion Optimization (RDO) of each input image…
The Loop Game: Quality Assessment and Optimization for Low-Light Image Enhancement
Danni Huang, Lingyu Zhu, Zihao Lin +3
There is an increasing consensus that the design and optimization of low light image enhancement methods need to be fully driven by perceptual quality. With numerous approaches pro…
Enhancing Low-Light Images in Real World via Cross-Image Disentanglement
Lanqing Guo, Renjie Wan, Wenhan Yang +2
Images captured in the low-light condition suffer from low visibility and various imaging artifacts, e.g., real noise. Existing supervised enlightening algorithms require a large s…
Towards Low Light Enhancement with RAW Images
Haofeng Huang, Wenhan Yang, Yueyu Hu +2
In this paper, we make the first benchmark effort to elaborate on the superiority of using RAW images in the low light enhancement and develop a novel alternative route to utilize…
Low-Light Image Enhancement with Normalizing Flow
Yufei Wang, Renjie Wan, Wenhan Yang +3
To enhance low-light images to normally-exposed ones is highly ill-posed, namely that the mapping relationship between them is one-to-many. Previous works based on the pixel-wise r…
Unpaired Image Enhancement with Quality-Attention Generative Adversarial Network
Zhangkai Ni, Wenhan Yang, Shiqi Wang +2
In this work, we aim to learn an unpaired image enhancement model, which can enrich low-quality images with the characteristics of high-quality images provided by users. We propose…
Learning End-to-End Lossy Image Compression: A Benchmark
Yueyu Hu, Wenhan Yang, Zhan Ma +1
Image compression is one of the most fundamental techniques and commonly used applications in the image and video processing field. Earlier methods built a well-designed pipeline,…
An Emerging Coding Paradigm VCM: A Scalable Coding Approach Beyond Feature and Signal
Sifeng Xia, Kunchangtai Liang, Wenhan Yang +2
In this paper, we study a new problem arising from the emerging MPEG standardization effort Video Coding for Machine (VCM), which aims to bridge the gap between visual feature comp…
Combining Progressive Rethinking and Collaborative Learning: A Deep Framework for In-Loop Filtering
Dezhao Wang, Sifeng Xia, Wenhan Yang +1
In this paper, we aim to address issues of (1) joint spatial-temporal modeling and (2) side information injection for deep-learning based in-loop filter. For (1), we design a deep…
Single Image Deraining: From Model-Based to Data-Driven and Beyond
Wenhan Yang, Robby T. Tan, Shiqi Wang +2
The goal of single-image deraining is to restore the rain-free background scenes of an image degraded by rain streaks and rain accumulation. The early single-image deraining method…
A Comprehensive Benchmark for Single Image Compression Artifacts Reduction
Jiaying Liu, Dong Liu, Wenhan Yang +3
We present a comprehensive study and evaluation of existing single image compression artifacts removal algorithms, using a new 4K resolution benchmark including diversified foregro…