paper-with-me

Video Enhancement

1개 벤치마크 · 논문 126편 · 이 태스크의 논문 보기 →

Benchmarks

MFQE v2

결과 6개

Most implemented

Video Enhancement with Task-Oriented Flow

2017-11-24 · 구현 4개

Papers

Diff-VF: Training-free High-quality Long Video Generation via Diffusion Model

2026-08-06 · Haoning Yang, Xinyuan Chen, Yaohui Wang, Guo Lu arxiv

Recently, diffusion models have made great progress in video generation. However, most existing video diffusion models are trained with short videos, and degrade when extrapolated to long videos, struggling to maintain l…

Video EnhancementVideo Generation

DiffCVE: Diffusion-based Compressed Video Enhancement

2026-07-08 · Wenqiang Xiao, Wenzhuo Ma, Junxi Zhang, Zhenzhong Chen arxiv

Perceptual quality enhancement of severely compressed videos remains challenging due to complex artifact patterns and substantial information loss. Recent diffusion models have demonstrated strong generative capability f…

Video Enhancement

EeveeDark: A Binary Neural Framework for Low-Light Video Enhancement via Event-Guided Sensor-Level Fusion

2026-07-07 · Onur Eker, Erkut Erdem, Aykut Erdem arxiv

Enhancing videos under extreme low-light conditions remains challenging due to the difficulty of balancing restoration quality and computational efficiency in resource-constrained settings. This paper introduces EeveeDar…

Computational EfficiencyVideo Enhancement

AnyMod-LLVE: Low-Light Video Enhancement with Modality-Agnostic Inference

2026-06-09 · Hangfeng Liang, Yutao Hu, Yanhan Hu, Xiaohan Wu 외 arxiv

Low-light video enhancement (LLVE) remains a challenging task due to severe information degradation under low-illumination conditions. Recent multimodal approaches have significantly improved enhancement performance by i…

Video Enhancement

BVI-Mamba: Video Enhancement Using a Visual State-Space Model for Low-Light and Underwater Environments

2026-04-26 · Guoxi Huang, Ruirui Lin, Yini Li, David R. Bull 외 arxiv

Videos captured in low-light and underwater conditions often suffer from distortions such as noise, low contrast, color imbalance, and blur. These issues not only limit visibility but also degrade automatic tasks like de…

Video Enhancement

ChopGrad: Pixel-Wise Losses for Latent Video Diffusion via Truncated Backpropagation

2026-03-18 · Dmitriy Rivkin, Parker Ewen, Lili Gao, Julian Ost 외 arxiv

Recent video diffusion models achieve high-quality generation through recurrent frame processing where each frame generation depends on previous frames. However, this recurrent mechanism means that training such models i…

Video Super-ResolutionVideo EnhancementVideo GenerationVideo Inpainting

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