GTA-HDR: A Large-Scale Synthetic Dataset for HDR Image Reconstruction

arXiv:2403.17837v1 Announce Type: cross
Abstract: High Dynamic Range (HDR) content (i.e., images and videos) has a broad range of applications. However, capturing HDR content from real-world scenes is expensive and time- consuming. Therefore, the challenging task of reconstructing visually accurate HDR images from their Low Dynamic Range (LDR) counterparts is gaining attention in the vision research community. A major challenge in this research problem is the lack of datasets, which capture diverse scene conditions (e.g., lighting, shadows, weather, locations, landscapes, …

arxiv cs.cv cs.gr cs.lg cs.mm dataset eess.iv gta image scale synthetic type