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arXiv Computer Vision By Lyuxing He, Daniel Guo, Elizabeth Terveen, Deepak Pathak, David Held, Tal Daniel

ParticleSplat: Self-supervised Object-centric Latent Particle Splatting

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ParticleSplat is a self‑supervised, object‑centric learning framework that extends the Deep Latent Particles (DLP) model into 3D by representing scenes as latent particles mapped to 3D Gaussian splats. It jointly encodes multiple camera views into a shared 3D latent space, enabling unsupervised learning of object masks and controllable 3D scene editing such as moving objects by manipulating latent particles. Experiments on simulated and real‑world datasets demonstrate that this 3D representation improves performance on downstream robotic manipulation tasks.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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