4 papers
RLDG: Robotic Generalist Policy Distillation via Reinforcement Learning
Charles Xu, Qiyang Li, Jianlan Luo +1
Recent advances in robotic foundation models have enabled the development of generalist policies that can adapt to diverse tasks. While these models show impressive flexibility, th…
InterNeRF: Scaling Radiance Fields via Parameter Interpolation
Clinton Wang, Peter Hedman, Polina Golland +2
Neural Radiance Fields (NeRFs) have unmatched fidelity on large, real-world scenes. A common approach for scaling NeRFs is to partition the scene into regions, each of which is ass…
RadSplat: Radiance Field-Informed Gaussian Splatting for Robust Real-Time Rendering with 900+ FPS
Michael Niemeyer, Fabian Manhardt, Marie-Julie Rakotosaona +7
Recent advances in view synthesis and real-time rendering have achieved photorealistic quality at impressive rendering speeds. While Radiance Field-based methods achieve state-of-t…
SMERF: Streamable Memory Efficient Radiance Fields for Real-Time Large-Scene Exploration
Daniel Duckworth, Peter Hedman, Christian Reiser +5
Recent techniques for real-time view synthesis have rapidly advanced in fidelity and speed, and modern methods are capable of rendering near-photorealistic scenes at interactive fr…