Deformable 2D Gaussian Splatting for Efficient 4K Video Compression
Ultra-High-Definition (UHD) video presents significant challenges for efficient storage and real-time decoding. Learning-based methods, such as Neural Video Compression (NVC) and Implicit Neural Representations (INR), achieve competitive rate-distortion performance but suffer from high decoding latency and excessive memory usage. Meanwhile, Gaussian Splatting has recently attracted attention in the computer graphics community due to its ultra-fast rendering and high-fidelity visual quality. Despite these advantages, its application in video compression remains largely unexplored. To bridge this gap, we propose a real-time video compression framework that represents and compresses a Group ...
| Authors | Chenhao Zhang, Fengqing Zhu |
|---|---|
| Primary category | eess.IV |
| Published | 12 September 2026 |
| Last updated at source | 12 September 2026 |
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