SOURCE-LINKED INTELLIGENCE
ParticleSplat: Self-supervised Object-centric Latent Particle Splatting
We present ParticleSplat, a self-supervised object-centric learning method that decomposes scenes into a set of latent ''particles'' representing semantic entities through feedforward 3D Gaussian Splatting. Building on the Deep Latent Particles (DLP) framework, which represents images as a set of particles with attributes such as position, scale, and visual appearance, we address a key limitation of DLP: its inherently 2D nature, which prevents explicit 3D spatial and geometric reasoning that are critical for downstream tasks such as robotic manipulation. Leveraging the structural similarity b
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-16T22:05:05.000Z
First collected: 2026-09-19T20:28:26.698Z. This is not the publication date.