Xiangyu Chen

TL;DR: The first challenge on high-dynamic range (HDR) imaging was part of the New Trends in Image Restoration and Enhancement (NTIRE) workshop, held in conjunction with CVPR 2021 as mentioned in this paper.

TL;DR: A novel Hybrid Attention Transformer (HAT) is proposed, which combines channel attention and self-attention schemes, thus making use of their complementary advantages and significantly outperforms the state-of-the-art methods.

TL;DR: This work proposes a novel learning-based approach using a spatially dynamic encoder-decoder network, HDRUNet, to learn an end-to-end mapping for single image HDR reconstruction with denoising and dequantization, which achieves the state-of-the-art performance in quantitative comparisons and visual quality.

TL;DR: The NTIRE 2022 challenge was to super-resolve an input image with a magnification factor of ×4 based on pairs of low and corresponding high resolution images and the aim was to design a network for single image super-resolution that achieved improvement of efficiency measured according to several metrics.

TL;DR: This paper reviews the challenge on constrained high dynamic range (HDR) imaging that was part of the New Trends in Image Restoration and Enhancement (NTIRE) workshop, held in conjunction with CVPR 2022, and the competition set-up, datasets, proposed methods and their results.