Awesome Deep HDR
A curated list of deep learning research papers and implementations for high dynamic range image and video synthesis.
What is Awesome Deep HDR?
Awesome-Deep-HDR is a curated repository of deep learning-based methods for high dynamic range image and video synthesis. It aggregates research papers, code implementations, and datasets focused on reconstructing HDR content from single or multiple low dynamic range inputs. The collection addresses key challenges in computer vision and graphics, such as motion handling, ghosting reduction, and real-time enhancement.
Computer vision researchers, graphics engineers, and deep learning practitioners working on HDR imaging, computational photography, or video enhancement tasks.
It provides a centralized, up-to-date index of state-of-the-art HDR techniques, saving time in literature review and offering direct access to papers, code, and datasets. The structured categorization by problem type (multi-view, single-image, video) helps users quickly find relevant methods for their specific needs.
Overview
A collection of deep learning based methods for HDR image synthesis
Use Cases
Best For
- Researchers surveying deep learning methods for HDR reconstruction
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