動的シーン向けのコンパクトな明示的4D表現
A Compact Explicit 4D Representation for Dynamic Scenes
単眼動画をスパースな4Dシーン状態に符号化するフィードフォワード自己符号化器Sparc4Dを提案し、新規視点合成と操作ポリシー学習の両方に活用できることを示した。
著者: Di Yang, Zhihao Li, Yanhai Xiong, Yufei Wang
分類: cs.CV
原文アブストラクト
A compact dynamic-scene representation must retain both the surfaces seen over time and the appearance needed to render them from new viewpoints. We present Sparc4D, a feed-forward autoencoder that encodes a monocular video with known cameras into a sparse 4D scene state. Static features are shared across the clip, while spatially anchored temporal slots store time-varying features with a median $5.0\times$ fewer values than per-frame storage and negligible change in the complete model's novel-view quality. A sparse decoder produces 2D Gaussian surfels, while stored source pixels preserve fine texture through geometric re-projection. The state includes one full source frame and dynamic-region pixels sampled every fourth frame, alongside learned features and sparse occupancy. For a 32-frame MultiCamVideo clip, it averages 0.67M 32-bit-equivalent values on random windows and 0.66M on the first-32 protocol. On first-32, Sparc4D reaches 21.97 dB, compared with 20.40 dB for MoVieS. On randomly placed windows, their PSNR scores are comparable. Without fine-tuning on real data, Sparc4D transfers to DyCheck and Neu3D, where stored texture improves LPIPS while slightly reducing PSNR. Frozen Sparc4D features also support a manipulation policy that reaches 81.3% success on ManiSkill3 StackCube from 1,000 demonstrations.