3 papers
cs.CV2026
Training-Free Model Ensemble for Single-Image Super-Resolution via Strong-Branch Compensation
Gengjia Chang, Xining Ge, Weijun Yuan +4
Single-image super-resolution has progressed from deep convolutional baselines to stronger Transformer and state-space architectures, yet the corresponding performance gains typica…
cs.CV2026
Beyond Model Design: Data-Centric Training and Self-Ensemble for Gaussian Color Image Denoising
Gengjia Chang, Xining Ge, Weijun Yuan +4
This paper presents our solution to the NTIRE 2026 Image Denoising Challenge (Gaussian color image denoising at fixed noise level ). Rather than proposing a new restoration…
cs.CV2026
The Fourth Challenge on Image Super-Resolution (4) at NTIRE 2026: Benchmark Results and Method Overview
Zheng Chen, Kai Liu, Jingkai Wang +150
This paper presents the NTIRE 2026 image super-resolution (4) challenge, one of the associated competitions of the NTIRE 2026 Workshop at CVPR 2026. The challenge aims to r…