tianyili2017/HEVC-Complexity-Reduction
Source programs to test the deep-learning-based complexity reduction approach for HEVC, at both intra- and inter-modes.
This project helps video engineers and researchers significantly speed up the HEVC video encoding process. It takes uncompressed YUV video files as input and uses deep learning to intelligently determine optimal video block partitions. This results in much faster encoding times for the same quality output, benefiting professionals working with HEVC video compression.
127 stars. No commits in the last 6 months.
Use this if you need to reduce the computational time for encoding HEVC video files using the HM 16.5 reference software, particularly for research and evaluation purposes.
Not ideal if you are looking for a standalone, user-friendly application for everyday video encoding or if you require compatibility with HEVC encoders other than HM 16.5.
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C++
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Jul 22, 2020
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