Abstract Neural Video Compression (NVC) has achieved remarkable performance in recent
years. However, precise rate control remains a challenge due to the inherent limitations of …

Natural image compression has been greatly improved in the deep learning era. However,
the compression performance will be heavily degraded if the pretrained encoder is directly …

Recent advances in implicit neural representation (INR)-based video coding have
demonstrated its potential to compete with both conventional and other learning-based …

Content-adaptive compression is crucial for enhancing the adaptability of the pre-trained
neural codec for various contents. Though, its application in neural video compression …

Video coding that pursues the highest compression efficiency is the art of computing for rate-
distortion optimization. The optimization has been approached in different ways, exemplified …

Video compression relies heavily on exploiting the temporal redundancy between video
frames, which is usually achieved by estimating and using the motion information. The …

Abstract Learning-based Neural Video Codecs (NVCs) have emerged as a compelling
alternative to standard video codecs, demonstrating promising performance, and simple and …

The learning-based video compression method has made significant progress in recent
years, exhibiting promising compression performance compared with traditional video …

The emerging large models have achieved notable progress in the fields of natural
language processing and computer vision. However, large models for neural video coding …

In Learned Video Compression (LVC), improving inter prediction, such as enhancing
temporal context mining and mitigating accumulated errors, is crucial for boosting rate …