2 citations · 2 across the 9 of their papers we have counts for
11 papers
NTIRE 2026 Low-light Enhancement: Twilight Cowboy Challenge
Aleksei Khalin, Egor Ershov, Artyom Panshin +46
This paper presents a review of the NTIRE 2026 Low-light Enhancement: Twilight Cowboy Challenge. The objective of the competition was to merge a set of misaligned smartphone images…
The Second LoViF 2026 Challenge on Real-World All-in-One Image Restoration: Methods and Results
Xiang Chen, Hao Li, Jiangxin Dong +89
This paper presents a review of the second LoViF Challenge on Real-World All-in-One Image Restoration. The challenge aims to advance unified image restoration under diverse real-wo…
MiM-DiT: MoE in MoE with Diffusion Transformers for All-in-One Image Restoration
Lingshun Kong, Jiawei Zhang, Zhengpeng Duan +6
All-in-one image restoration is challenging because different degradation types, such as haze, blur, noise, and low-light, impose diverse requirements on restoration strategies, ma…
A Diffusion-Based Framework for Occluded Object Movement
Zheng-Peng Duan, Jiawei Zhang, Siyu Liu +5
Seamlessly moving objects within a scene is a common requirement for image editing, but it is still a challenge for existing editing methods. Especially for real-world images, the…
GSV3D: Gaussian Splatting-based Geometric Distillation with Stable Video Diffusion for Single-Image 3D Object Generation
Ye Tao, Jiawei Zhang, Yahao Shi +2
Image-based 3D generation has vast applications in robotics and gaming, where high-quality, diverse outputs and consistent 3D representations are crucial. However, existing methods…
DiT4SR: Taming Diffusion Transformer for Real-World Image Super-Resolution
Zheng-Peng Duan, Jiawei Zhang, Xin Jin +6
Large-scale pre-trained diffusion models are becoming increasingly popular in solving the Real-World Image Super-Resolution (Real-ISR) problem because of their rich generative prio…
DeblurDiff: Real-World Image Deblurring with Generative Diffusion Models
Lingshun Kong, Jiawei Zhang, Dongqing Zou +4
Diffusion models have achieved significant progress in image generation. The pre-trained Stable Diffusion (SD) models are helpful for image deblurring by providing clear image prio…
Semantic Segmentation Prior for Diffusion-Based Real-World Super-Resolution
Jiahua Xiao, Jiawei Zhang, Dongqing Zou +3
Real-world image super-resolution (Real-ISR) has achieved a remarkable leap by leveraging large-scale text-to-image models, enabling realistic image restoration from given recognit…
Enhancing Safety in Reinforcement Learning with Human Feedback via Rectified Policy Optimization
Xiyue Peng, Hengquan Guo, Jiawei Zhang +4
Balancing helpfulness and safety (harmlessness) is a critical challenge in aligning large language models (LLMs). Current approaches often decouple these two objectives, training s…
DiffRetouch: Using Diffusion to Retouch on the Shoulder of Experts
Zheng-Peng Duan, Jiawei zhang, Zheng Lin +4
Image retouching aims to enhance the visual quality of photos. Considering the different aesthetic preferences of users, the target of retouching is subjective. However, current re…
Diffusion-based Blind Text Image Super-Resolution
Yuzhe Zhang, Jiawei Zhang, Hao Li +4
Recovering degraded low-resolution text images is challenging, especially for Chinese text images with complex strokes and severe degradation in real-world scenarios. Ensuring both…