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arXiv AI By Yingwen Zhang, Meng Wang, Liqiang He, Shiqi Wang

Can LLMs Design Video Coding Tools? A Case Study on Planar Mode

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The paper investigates whether large language models (LLMs) can design video coding tools, focusing on the Planar mode used in video coding standards. Using a generation-and-evaluation loop, the LLM generates new Planar predictors, which are then tested in the Fraunhofer Versatile Video Encoder (VVenC) and the Enhanced Compression Model (ECM). Results show that the LLM-generated mode can outperform the conventional Planar mode, achieving a 0.18% bitrate saving with a 0.4% complexity increase, and that similar gains are possible when integrating the new predictor into ECM under low‑resolution settings.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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