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Xinran Yang

4 accepted papers

2026

LoG3D: Ultra-High-Resolution 3D Shape Modeling via Local-to-Global Partitioning

CVPR 2026

Generating high-fidelity 3D contents remains a fundamental challenge due to the complexity of representing arbitrary topologies--such as open surfaces and intricate internal structures--while preserving geometric details. Prevailing methods based on signed distance fields (SDFs) are hampered by cost

Cited by 0SourceScholar
2025

CharacterCraft: Bridging the Literature-Reality Dialogue Gap for Practical Role-Playing Agents

EMNLP 2025

Recent advancements in large language models (LLMs) have given rise to the emergence of role-playing agents (RPAs). The development of high-quality dialogue datasets is critical for advancing RPAs. However, existing datasets have two main issues: (1) the bias between query distributions and real-wor

2025

EdgeMovingNet: Edge-preserving Point Cloud Reconstruction via Joint Geometry Features

CVPR 2025poster

Point cloud reconstruction is a critical process in 3D representation and reverse engineering. When it comes to CAD models, edges are significant features that play a crucial role in characterizing the geometry of 3D shapes. However, few points are exactly sampled on edges during acquisition, result…

Cited by 0SourcePDFScholar
2025

SGCR: Spherical Gaussians for Efficient 3D Curve Reconstruction

CVPR 2025poster

Neural rendering techniques have made substantial progress in generating photo-realistic 3D scenes. The latest 3D Gaussian Splatting technique has achieved high quality novel view synthesis as well as fast rendering speed. However, 3D Gaussians lack proficiency in defining accurate 3D geometric stru…