SOURCE-LINKED INTELLIGENCE
Beyond Visual Quality: Evaluating Physical Consistency under Ego-Motion with EgoGenEval
Recent visual generators produce high-fidelity images yet often violate physical consistency under ego-motion, limiting their use for spatial reasoning and embodied planning. Existing benchmarks largely focus on isolated images or single-step quality, leaving this challenge underexplored. We introduce EgoGenEval, a geometry-grounded, pose-free benchmark designed to evaluate the physical consistency of visual generators under ego-motion, and organize our study into two parts. (1) EgoGenEval contains 1,400 cases and 2,360 target views spanning single-step and multi-step ego-motion. It separately
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- arXiv · AI, language, vision and robotics · 2026-09-10T07:19:50.000Z
First collected: 2026-09-20T19:12:12.556Z. This is not the publication date.