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In the "Draft Paper" version or the supplemental materials of this research:
The filename is a specific asset used in the research paper "Deep Bilateral Learning for Real-Time Image Enhancement" by Gharbi et al. (presented at SIGGRAPH 2017). HD - video60HD.mp4
The video illustrates the from a professional retouching example to raw footage. In the "Draft Paper" version or the supplemental
It highlights the lack of "flicker" or temporal artifacts, a common issue in frame-by-frame video processing that this specific method solves using its bilateral grid approach. It highlights the lack of "flicker" or temporal
: "video60HD.mp4" is often cited in discussions regarding real-time video processing because it demonstrates that high-quality image enhancement doesn't require high-resolution intermediate layers, saving significant computational power. Context of the File
It serves as a benchmark video to demonstrate the efficiency and quality of their deep learning model, which performs real-time photo retouching and enhancement. Key Details from the Paper