Image and video generators can produce spatially consistent visual content, but how to use this capability to improve spatial understanding remains underexplored. We study this problem from two perspe
GeoUG improves spatial reasoning by combining depth and multi-view generation with adaptive geometric verification during inference.
Image and video generators can produce spatially consistent visual content, but how to use this capability to improve spatial understanding remains underexplored. We study this problem from two perspectives: geometric supervision during training and explicit geometric evidence during inference. To this end, we introduce a unified geometric understanding and generation model (GeoUG) that integrates depth and multi-view generation with spatial understanding. First, we design a multi-scale depth codec that enables metric-depth generation using a pretrained visual autoencoder, and show that joint training yields task-dependent gains in spatial understanding. Second, we introduce 3DCueBench to…
Summary and abstract excerpt via Hugging Face Papers ↗ · arXiv.
Learning and Reasoning with Geometry: How Generation Helps Spatial Understanding was first seen on Hugging Face · Daily papers on Oct 30, 2026. Since then it has appeared in 1 check on 1 different day. Its best position was #30 of 30, reached on Oct 30, 01:28 UTC. It dropped off the list after Oct 30, 01:28 UTC.
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Not at the moment. It was last on the list on Oct 30, 01:28 UTC, after 1 day of trending.
#30 on Hugging Face · Daily papers, on Oct 30, 01:28 UTC. Trendoday checks this list every 120 minutes.
It was first seen on Oct 30, 2026 and has been on the list on 1 day (1 check) since.