A Compact Dynamic 3D Gaussian Representation for Real-Time Dynamic View Synthesis

November 21, 2023 Β· Declared Dead Β· πŸ› European Conference on Computer Vision

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Authors Kai Katsumata, Duc Minh Vo, Hideki Nakayama arXiv ID 2311.12897 Category cs.GR: Graphics Citations 42 Venue European Conference on Computer Vision Last Checked 6 months ago
Abstract
3D Gaussian Splatting (3DGS) has shown remarkable success in synthesizing novel views given multiple views of a static scene. Yet, 3DGS faces challenges when applied to dynamic scenes because 3D Gaussian parameters need to be updated per timestep, requiring a large amount of memory and at least a dozen observations per timestep. To address these limitations, we present a compact dynamic 3D Gaussian representation that models positions and rotations as functions of time with a few parameter approximations while keeping other properties of 3DGS including scale, color and opacity invariant. Our method can dramatically reduce memory usage and relax a strict multi-view assumption. In our experiments on monocular and multi-view scenarios, we show that our method not only matches state-of-the-art methods, often linked with slower rendering speeds, in terms of high rendering quality but also significantly surpasses them by achieving a rendering speed of $118$ frames per second (FPS) at a resolution of 1,352$\times$1,014 on a single GPU.
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