Technique Report of CVPR 2024 PBDL Challenges
FOS: Computer and information sciences
Computer Vision and Pattern Recognition (cs.CV)
Computer Science - Computer Vision and Pattern Recognition
DOI:
10.48550/arxiv.2406.10744
Publication Date:
2024-06-15
AUTHORS (102)
ABSTRACT
The intersection of physics-based vision and deep learning presents an exciting frontier for advancing computer technologies. By leveraging the principles physics to inform enhance models, we can develop more robust accurate systems. Physics-based aims invert processes recover scene properties such as shape, reflectance, light distribution, medium from images. In recent years, has shown promising improvements various tasks, when combined with vision, these approaches robustness accuracy This technical report summarizes outcomes Physics-Based Vision Meets Deep Learning (PBDL) 2024 challenge, held in CVPR workshop. challenge consisted eight tracks, focusing on Low-Light Enhancement Detection well High Dynamic Range (HDR) Imaging. details objectives, methodologies, results each track, highlighting top-performing solutions their innovative approaches.
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