Converting video formats with FFmpeg

By S. Tomar. 2006

560 citations recorded by the source corpus.

How researchers see this paper

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NeRV: Neural Representations for Videos (2021, methodology): “3 Implementation Details of Baselines Following prior works, we used ffmpeg [2] to produce the evaluation metrics for H.”
Variable Bitrate Discrete Neural Representations via Causal Self-Attention (2021, methodology): “As a baseline, we compare against MP3 —an industry-standard for lossy audio compression that supports full-ﬁle encoding at different bitrates. b i outputs are encoded using FFmpeg [29] set to b i .”
JESC: Japanese-English Subtitle Corpus (2017, methodology): “We then used the ffmpeg library to convert ﬁles into a common Sub-Rip ( .srt ) format (Tomar, 2006).”
Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets (2023, methodology): “We clip the videos using FFMPEG [91] directly after cut detection by extracting the times-tamps of the keyframes in the source videos and snapping detected cuts onto the closest keyframe timestamp, which does not cross the detected cut.”