BEGIN:VCALENDAR VERSION:2.0 PRODID:Linklings LLC BEGIN:VTIMEZONE TZID:Asia/Tokyo X-LIC-LOCATION:Asia/Tokyo BEGIN:STANDARD TZOFFSETFROM:+0900 TZOFFSETTO:+0900 TZNAME:JST DTSTART:18871231T000000 END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20250110T023312Z LOCATION:Hall B7 (1)\, B Block\, Level 7 DTSTART;TZID=Asia/Tokyo:20241203T172800 DTEND;TZID=Asia/Tokyo:20241203T174000 UID:siggraphasia_SIGGRAPH Asia 2024_sess111_papers_539@linklings.com SUMMARY:V^3: Viewing Volumetric Videos on Mobiles via Streamable 2D Dynami c Gaussians DESCRIPTION:Technical Papers\n\nPenghao Wang, Zhirui Zhang, Liao Wang, Kai xin Yao, and Siyuan Xie (ShanghaiTech University, NeuDim Inc.); Jingyi Yu (ShanghaiTech University); Minye Wu (KU Leuven); and Lan Xu (ShanghaiTech University)\n\nExperiencing high-fidelity volumetric video as seamlessly a s 2D videos is a long-held dream. However, current dynamic 3DGS methods, d espite their high rendering quality, face challenges in streaming on mobil e devices due to computational and bandwidth constraints. In this paper, w e introduce V3 (Viewing Volumetric Videos), a novel approach that enables high-quality mobile rendering through the streaming of dynamic Gaussians. Our key innovation is to view dynamic 3DGS as 2D videos, facilitating the use of hardware video codecs. Additionally, we propose a two-stage trainin g strategy to reduce storage requirements with rapid training speed. The f irst stage employs hash encoding and shallow MLP to learn motion, then red uces the number of Gaussians through pruning to meet the streaming require ments, while the second stage fine-tunes other Gaussian attributes using r esidual entropy loss and temporal loss to improve temporal continuity. Thi s strategy, which disentangles motion and appearance, maintains high rende ring quality with compact storage requirements. Meanwhile, we designed a m ulti-platform player to decode and render 2D Gaussian videos. Extensive ex periments demonstrate the effectiveness of V3, outperforming other methods by enabling high-quality rendering and streaming on common devices, which is unseen before. As the first to stream dynamic Gaussians on mobile devi ces, our companion player offers users an unprecedented volumetric video e xperience, including smooth scrolling and instant sharing.\n\nRegistration Category: Full Access, Full Access Supporter\n\nLanguage Format: English Language\n\nSession Chair: Yifan Peng (University of Hong Kong) URL:https://asia.siggraph.org/2024/program/?id=papers_539&sess=sess111 END:VEVENT END:VCALENDAR