arXiv:2504.12276
공식 코드 · Papers with Code
The Tenth NTIRE 2025 Image Denoising Challenge Report
원문 초록
This paper presents an overview of the NTIRE 2025 Image Denoising Challenge ({\sigma} = 50), highlighting the proposed methodologies and corresponding results. The primary objective is to develop a network architecture capable of achieving high-quality denoising performance, quantitatively evaluated using PSNR, without constraints on computational complexity or model size. The task assumes independent additive white Gaussian noise (AWGN) with a fixed noise level of 50. A total of 290 participants registered for the challenge, with 20 teams successfully submitting valid results, providing insights into the current state-of-the-art in image denoising.
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Energy-Based Transformers are Scalable Learners and Thinkers
STAR-Net: An Interpretable Model-Aided Network for Remote Sensing Image Denoising
Optimal Density Functions for Weighted Convolution in Learning Models
Optimal Weighted Convolution for Classification and Denosing
Learning Multi-scale Spatial-frequency Features for Image Denoising
A Real-time Endoscopic Image Denoising System
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