AIM 2025 challenge on Inverse Tone Mapping Report: Methods and Results
By: Chao Wang , Francesco Banterle , Bin Ren and more
Potential Business Impact:
Makes normal pictures look like super bright ones.
This paper presents a comprehensive review of the AIM 2025 Challenge on Inverse Tone Mapping (ITM). The challenge aimed to push forward the development of effective ITM algorithms for HDR image reconstruction from single LDR inputs, focusing on perceptual fidelity and numerical consistency. A total of \textbf{67} participants submitted \textbf{319} valid results, from which the best five teams were selected for detailed analysis. This report consolidates their methodologies and performance, with the lowest PU21-PSNR among the top entries reaching 29.22 dB. The analysis highlights innovative strategies for enhancing HDR reconstruction quality and establishes strong benchmarks to guide future research in inverse tone mapping.
Similar Papers
AIM 2025 challenge on Inverse Tone Mapping Report: Methods and Results
CV and Pattern Recognition
Makes normal pictures look like super bright, colorful ones.
AIM 2025 Low-light RAW Video Denoising Challenge: Dataset, Methods and Results
CV and Pattern Recognition
Cleans up dark, grainy videos from phones.
Efficient Real-World Deblurring using Single Images: AIM 2025 Challenge Report
CV and Pattern Recognition
Makes blurry photos clear with less computer power.