The Neverwhere Visual Parkour Benchmark Suite

arXiv:2609.16443 · cs.RO, cs.CV, cs.LG · Submitted 2026-09-14 · Read on arXiv

cs.RO, cs.CV, cs.LG

Submitted: 2026-09-14

Updated: 2026-09-14

Comments: 9 pages, 14 figures. Accepted to IROS 2026. Project page: https://ziyc.github.io/neverwhere-bench/

Code: https://github.com/vuer-ai/vuer

Project page: https://ziyc.github.io/neverwhere-bench

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Benchmark — 23× in this paper · explained in 2 episodes
• Gaussian Splatting — 11× in this paper · explained in 4 episodes
• Fidelity — 5× in this paper · explained in 2 episodes
• 3D Gaussian Splatting — 4× in this paper · explained in 2 episodes
• Ablation — 4× in this paper · explained in 1 episode
• Generalization — 4× in this paper · explained in 13 episodes
• Alignment — 3× in this paper · explained in 1 episode
• Calibration — 3× in this paper · explained in 7 episodes
• Digital Twin — 3× in this paper · explained in 5 episodes
• Accuracy — 2× in this paper · explained in 1 episode
• Action Space — 2× in this paper · explained in 1 episode
• Embodied AI — 2× in this paper · explained in 2 episodes
• Generative Model — 2× in this paper · explained in 2 episodes
• Generative Models — 2× in this paper · explained in 2 episodes
• Point Clouds — 2× in this paper · explained in 2 episodes
• Regularization — 2× in this paper · explained in 3 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Action Chunking — 1× in this paper · explained in 1 episode
• Clustering — 1× in this paper · explained in 2 episodes
• Conference on Computer Vision and Pattern Recognition — 1× in this paper
• Consistency — 1× in this paper · explained in 3 episodes
• Diffusion Model — 1× in this paper · explained in 8 episodes
• Diffusion Models — 1× in this paper · explained in 6 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Unified Framework — 1× in this paper · explained in 5 episodes
• World Model — 1× in this paper · explained in 7 episodes
• Zero-Shot Transfer — 1× in this paper · explained in 4 episodes

Sources

• ManiSkill3: GPU Parallelized Robotics Simulation and Rendering for Generalizable Embodied AI
• RoboCasa: Large-Scale Simulation of Everyday Tasks for Generalist Robots
• RLBench: The Robot Learning Benchmark & Learning Environment
• RoboHive: A Unified Framework for Robot Learning
• OmniRe: Omni Urban Scene Reconstruction
• VR-Robo: A Real-to-Sim-to-Real Framework for Visual Robot Navigation and Locomotion
• GaussGym: An open-source real-to-sim framework for learning locomotion from pixels
• GSWorld: Closed-Loop Photo-Realistic Simulation Suite for Robotic Manipulation
• Cosmos Policy: Fine-Tuning Video Models for Visuomotor Control and Planning
• Evaluating Gemini Robotics Policies in a Veo World Simulator
• GreenScan: Towards large-scale terrestrial monitoring the health of urban trees using mobile sensing
• Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs
• Extreme Parkour with Legged Robots
• Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware

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