AI RESEARCH
Lotus-2: Advancing Geometric Dense Prediction with Powerful Image Generative Model
arXiv CS.CV
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ArXi:2512.01030v3 Announce Type: replace Recovering pixel-wise geometric properties from a single image is fundamentally ill-posed due to appearance ambiguity and non-injective mappings between 2D observations and 3D structures. While discriminative regression models achieve strong performance through large-scale supervision, their success is bounded by the scale, quality, and diversity of available data, as well as by limited physical reasoning.