Implicit Surface Compression - with Good Old Discrete Cosine Transform and Motion Compensation
Tao Jin, Shengxi Wu, Tianshu Huang, Mallesham Dasari, Srinivasan Seshan, Anthony Rowe
Abstract
The rapid adoption of volumetric capture technologies has created a pressing need for efficient storage and streaming of dynamic 3D content. Unfortunately, current compression standards often treat dynamic sequences as independent frames or rely on computationally expensive non-rigid registration, making them unsuitable for real-time applications or large-scale environments. In this paper, we present a novel end-to-end compression framework for dynamic Truncated Signed Distance Field volumes derived from captured 3D content, leveraging a representation that is temporally stable, easily parallelizable, and already widely used in scene reconstruction and volumetric fusion pipelines. We then adapt classic 2D video coding paradigms such as spatial coding via Discrete Cosine Transform and temporal coding using a real-time motion compensation pipeline to provide robust, real-time, and training-free encoding and decoding for 3D content. Extensive evaluations on human performance captures demonstrate that our codec achieves 35% bitrate savings at equal distortion while operating in real time at 30 FPS, while stronger temporal coherence in large-scale synthetic environments yields up to 12× bitrate reduction at equal distortion.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext c938dede-44e3-49de-ac30-9eef9ba6b33eBuilds on9
- 3D Gaussian Splatting for Real-Time Radiance Field RenderingBernhard Kerbl, Georgios Kopanas, Thomas Leimkühler, George DrettakisSIGGRAPH 2023 · 5,687 citations
- Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance FieldsJonathan T. Barron, Ben Mildenhall, Matthew Tancik, Peter Hedman et al.ICCV 2021 · 2,700 citations
- NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view ReconstructionPeng Wang, Lingjie Liu, Yuan Liu, Christian Theobalt et al.NeurIPS 2021 · 2,500 citations
- UNISURF: Unifying Neural Implicit Surfaces and Radiance Fields for Multi-View ReconstructionMichael Oechsle, Songyou Peng, Andreas GeigerICCV 2021 · 885 citations
- Depth Anything: Unleashing the Power of Large-Scale Unlabeled DataLihe Yang, Bingyi Kang, Zilong Huang, Xiaogang Xu et al.CVPR 2024 · 847 citations
Related papers
- Deep Implicit Volume CompressionDanhang Tang, Saurabh Singh, Philip A. Chou, Christian Häne et al.CVPR 2020
- TSMC: Time-varying 4D Scene Mesh CompressionGuodong Chen, Libor Vása, Amrita Mazumdar, Mallesham DasariSIGGRAPH 2026
- TSDF-Based Efficient Motion-Compensated Temporal Interpolation for 3D Dynamic SequencesSoowoong Kim, Minseong Kwon, Junho Choi, Gun Bang et al.AAAI 2025 · 1 citation
- SmoothMotionVectors: Optimizing Your Content for Video Codecs in Free View Video CompressionMingyang Song, Yang Zhang, Siyu Tang, Tunç Ozan AydinSIGGRAPH 2026
- Temporal Smoothness-Aware Rate-Distortion Optimized 4D Gaussian SplattingHyeongmin Lee, Kyungjune BaekNeurIPS 2025 · 3 citations
