AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
TL;DR
The results suggest that observation noise and single-view geometric ambiguity, rather than model expressiveness, are the primary limiting factors for monocular soccer reconstruction.
World models offer a data-driven alternative to traditional simulators for robotics, with applications spanning policy evaluation, improvement, and planning. All of these uses depend on faithful 3D geometry, yet current video-based world models are trained on RGB alone and produce rollouts that look correct frame-by-fr...
RoboPhys-3D, a 3D-grounded EWM benchmark built on RoboTwin 2.0, is introduced, and Average Full Score, a hierarchical score averaging all 50 metrics for comprehensive evaluation, and RoboPhyscore, a compact task-aligned score averaging the metrics most strongly correlated with task success are introduced.
RididBench is introduced, a simulator-grounded benchmark that compares a generated continuation with a reference rollout from the same initial frame and motion description, with per-frame masks, depth, 6-DoF trajectories, and contacts available for scoring.
This work presents a systematic compute-platform benchmark of neural 3D reconstruction methods, evaluating NeRF and 3D Gaussian Splatting training and rendering on GPU-enabled computing devices, and place Meta's SAM3D single-image reconstruction on the same axes to quantify its latency and fidelity gap relative to per-...
VI3, a model-agnostic framework that metrically anchors a pretrained 3DFM using only IMU readings, is introduced, acting as a fine refinement under well-conditioned motion and as a strong prior when motion is less informative.
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