Dusting the Phantom: Gaussian Allocation for Fading Dynamic Content
Dynamic Gaussian representations have made high-quality, real-time volumetric video increasingly practical, yet challenging motion can still break their reconstruction: small fast-moving objects may disappear, and fine textures in highly dynamic regions are often lost. In particular, simply training longer or using more Gaussians may still fail to recover small, fast-moving objects. We argue that the key bottleneck is not representational capacity itself, but where and when Gaussian primitives are allocated. Existing allocation strategies rely on current Gaussian locations and often overlook the spatiotemporal destinations of relocated Gaussians. To address these limitations, we introduce...
| Authors | Minhyeok Roh, Minseo Lee, Jun Young Jeong et al. |
|---|---|
| Primary category | cs.CV |
| Published | 15 October 2026 |
| Last updated at source | 15 October 2026 |
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