#geometric-modeling News & Analysis

3 articles tagged with #geometric-modeling. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

3 articles

AINeutralarXiv – CS AI · Jun 96/10

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CLONE: A 3DGS-Based Closed-Loop Differentiable Optimization Framework for Single-Image Normal Estimation

Researchers introduce CLONE, a 3D Gaussian Splatting-based framework that estimates surface normals from single images by creating a closed-loop differentiable optimization pathway. The method unifies discriminative and generative approaches through an image-geometry-image consistency loop, eliminating the need for explicit normal supervision while maintaining geometric accuracy and local detail.

AINeutralarXiv – CS AI · Jun 85/10

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A Geometric Gaussian Mixture Representation of Plane Curves

Researchers introduce a Gaussian Mixture Model (GMM) framework that represents plane curves as probabilistic geometric primitives, encoding both tangential and normal uncertainty. This mathematical approach enables uncertainty-aware geometric modeling applicable to CAD, robotics, and digital twin applications.

AIBullisharXiv – CS AI · Jun 46/10

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GeoMin: Data-Efficient Semi-Supervised RLVR via Geometric Distribution Modeling

GeoMin, a new semi-supervised reinforcement learning method, advances LLM reasoning by using geometric distribution modeling to better utilize unlabeled data. The approach achieves 4.1% performance gains over existing methods and matches fully supervised models with only 10% of the annotation data, significantly improving data efficiency in AI training.