The Neverwhere Visual Parkour Benchmark Suite
Read the original on arXiv Machine Learning →The paper introduces the Neverwhere Visual Parkour Benchmark Suite, a collection of over sixty hyper‑photo‑realistic 3D Gaussian Splatting reconstructions of urban indoor and outdoor scenes designed to evaluate visual locomotion controllers in closed‑loop, continuous testing setups. It aims to bridge the gap between training and real‑world evaluation by providing reproducible environments and policy checkpoints trained across multiple scenes, while highlighting the risks of relying solely on 3D Gaussian‑generated data. The authors offer code and data on their project page for easy integration into robotic evaluation pipelines.
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 Machine Learning.