Enhancing Neural Video Compression of Static Scenes with Positive-Incentive Noise
Static scene videos, such as surveillance feeds and videotelephony streams, constitute a dominant share of storage consumption and network traffic. However, both traditional standardized codecs and neural video compression (NVC) methods struggle to encode these videos efficiently due to inadequate usage of temporal redundancy and severe distribution gaps between training and test data, respectively. While recent generative compression methods improve perceptual quality, they introduce hallucinated details that are unacceptable in authenticity-critical applications. To overcome these limitations, we propose a positive-incentive camera (PIC) framework for static scene videos, where short-te...
| Authors | Cheng Yuan, Zhenyu Jia, Jiawei Shao et al. |
|---|---|
| Primary category | eess.IV |
| Published | 6 March 2026 |
| Last updated at source | 27 March 2026 |
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