SOURCE-LINKED INTELLIGENCE
SplashSplat: Reconstructing Splashing Liquids from Real-World Multi-View Videos
A splash lives for a fraction of a second: sheets tear into ligaments and droplets, appearance is view-dependent and nearly textureless, and little persists long enough to track. Reconstruction research has consequently focused on smoke, synthetic liquids, or gently deforming surfaces. To our knowledge, no synchronized multi-view dataset of splashing liquids exists. We therefore introduce a benchmark of 20 real scenes, from coherent streams to violent splashes, captured by seven synchronized, calibrated 4K cameras at 60 fps, with manually refined per-view liquid and container masks and fixed e
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-17T17:59:41.000Z
First collected: 2026-09-19T20:28:14.107Z. This is not the publication date.