NTIRE 2024 Challenge on Low Light Image Enhancement: Methods and Results
원문 초록
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 network design or solution capable of generating brighter, clearer, and visually appealing results when dealing with a variety of conditions, including ultra-high resolution (4K and beyond), non-uniform illumination, backlighting, extreme darkness, and night scenes. A notable total of 428 participants registered for the challenge, with 22 teams ultimately making valid submissions. This paper meticulously evaluates the state-of-the-art advancements in enhancing low-light images, reflecting the significant progress and creativity in this field.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
LENVIZ: A High-Resolution Low-Exposure Night Vision Benchmark Dataset
HVI-CIDNet+: Beyond Extreme Darkness for Low-Light Image Enhancement
RT-X Net: RGB-Thermal cross attention network for Low-Light Image Enhancement
URWKV: Unified RWKV Model with Multi-state Perspective for Low-light Image Restoration
See through the Dark: Learning Illumination-affined Representations for Nighttime Occupancy Prediction
Degradation-Aware Feature Perturbation for All-in-One Image Restoration
토론
이 논문과 연결된 포럼 글이 아직 없습니다.