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Txt2Vid: Ultra-Low Bitrate «Generative Compression» of Talking-Head Videos to Text

День 3


Video represents the majority of internet traffic today leading to a continuous technological arms race between generating higher quality content, transmitting larger file sizes and supporting network infrastructure. Adding to this is the recent COVID-19 pandemic fueled surge in the use of video conferencing tools. Since videos take up substantial bandwidth (~100 Kbps to few Mbps), improved video compression can have a substantial impact on network performance for live and pre-recorded content, providing broader access to multimedia content worldwide. In this talk, speaker will mainly focus on a novel video compression pipeline, called Txt2Vid, which substantially reduces data transmission rates by compressing webcam videos ("talking-head videos") to a text transcript. The text is transmitted and decoded into a realistic reconstruction of the original video using recent advances in deep learning based voice cloning and lip syncing models. Our generative pipeline achieves two to three orders of magnitude reduction in the bitrate as compared to the standard audio-video codecs (encoders-decoders), while maintaining equivalent Quality-of-Experience based on a subjective evaluation. The Txt2Vid framework opens up the potential for creating novel applications such as enabling audio-video communication during poor internet connectivity, or in remote terrains with limited bandwidth. Pulkit will also talk about our ideas and learnings from two other projects on enabling low-bitrate communication, viz. "human are awesome compressors" and "using keypoint extraction and digital puppetry".

  • #ml
  • #voice_processing
  • #deep_learning


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