18 citations · 44 across the 11 of their papers we have counts for
11 papers
DPC-Net: Dual-Prior Collaborative Network for All-in-One Image Restoration
Zhaokun He, Kangbiao Shi, Axi Niu +4
All-in-One Image Restoration (AiOIR) aims to handle diverse degradations within a unified model. However, existing methods often overlook image semantics in degradation modeling an…
Self-Reasoning Agentic Framework for Narrative Product Grid-Collage Generation
Minyan Luo, Yuxin Zhang, Yifei Li +5
Narrative-driven product photography has become a prevalent paradigm in modern marketing, as coherent visual storytelling helps convey product value and establishes emotional engag…
UniBlendNet: Unified Global, Multi-Scale, and Region-Adaptive Modeling for Ambient Lighting Normalization
Jiatao Dai, Wei Dong, Han Zhou +2
Ambient Lighting Normalization (ALN) aims to restore images degraded by complex, spatially varying illumination conditions. Existing methods, such as IFBlend, leverage frequency-do…
NTIRE 2026 The 3rd Restore Any Image Model (RAIM) Challenge: Professional Image Quality Assessment (Track 1)
Guanyi Qin, Jie Liang, Bingbing Zhang +50
In this paper, we present an overview of the NTIRE 2026 challenge on the 3rd Restore Any Image Model in the Wild, specifically focusing on Track 1: Professional Image Quality Asses…
PaAgent: Portrait-Aware Image Restoration Agent via Subjective-Objective Reinforcement Learning
Yijian Wang, Qingsen Yan, Jiantao Zhou +2
Image Restoration (IR) agents, leveraging multimodal large language models to perceive degradation and invoke restoration tools, have shown promise in automating IR tasks. However,…
HVI: A New Color Space for Low-light Image Enhancement
Qingsen Yan, Yixu Feng, Cheng Zhang +6
Low-Light Image Enhancement (LLIE) is a crucial computer vision task that aims to restore detailed visual information from corrupted low-light images. Many existing LLIE methods ar…
Bracketing Image Restoration and Enhancement with High-Low Frequency Decomposition
Genggeng Chen, Kexin Dai, Kangzhen Yang +7
In real-world scenarios, due to a series of image degradations, obtaining high-quality, clear content photos is challenging. While significant progress has been made in synthesizin…
NTIRE 2024 Challenge on Low Light Image Enhancement: Methods and Results
Xiaoning Liu, Zongwei Wu, Ao Li +109
This paper reviews the NTIRE 2024 low light image enhancement challenge, highlighting the proposed solutions and results. The aim of this challenge is to discover an effective netw…
CRNet: A Detail-Preserving Network for Unified Image Restoration and Enhancement Task
Kangzhen Yang, Tao Hu, Kexin Dai +6
In real-world scenarios, images captured often suffer from blurring, noise, and other forms of image degradation, and due to sensor limitations, people usually can only obtain low…
You Only Need One Color Space: An Efficient Network for Low-light Image Enhancement
Qingsen Yan, Yixu Feng, Cheng Zhang +5
Low-Light Image Enhancement (LLIE) task tends to restore the details and visual information from corrupted low-light images. Most existing methods learn the mapping function betwee…
Towards High-quality HDR Deghosting with Conditional Diffusion Models
Qingsen Yan, Tao Hu, Yuan Sun +5
High Dynamic Range (HDR) images can be recovered from several Low Dynamic Range (LDR) images by existing Deep Neural Networks (DNNs) techniques. Despite the remarkable progress, DN…