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cs.CV2026

SmartMage: Dynamic Modality Orchestration for 3D Scene Understanding

Yue Zhang, Yingzhao Jian, Yunqiu Xu +2

Understanding 3D scenes is fundamental to embodied intelligence, requiring joint reasoning over heterogeneous information from multiple modalities, including visual and geometric c…

cs.CV2026

Depth Estimators Are Implicit Neural Fields for 3D Scene Geometry Inpainting and Reconstruction

Yingzhao Jian, Zihao Lin, Hehe Fan

The 3D geometry of real-world scene data is often incomplete. Mainstream methods use depth estimators to inpaint missing structure. However, their prediction results can be inconsi…

cs.CV2026

Skill-3D: Evolving Scene-Aware Skills for Agentic 3D Spatial Reasoning

Haoyuan Li, Zhengdong Hu, Jun Wang +2

This paper explores agentic 3D spatial understanding, i.e., MLLM agents performing 3D reasoning through tool use. Existing methods often misuse tools and exhibit biased tool prefer…

cs.CV2026

Stroke3D: Lifting 2D strokes into rigged 3D model via latent diffusion models

Ruisi Zhao, Haoren Zheng, Zongxin Yang +2

Rigged 3D assets are fundamental to 3D deformation and animation. However, existing 3D generation methods face challenges in generating animatable geometry, while rigging technique…

cs.CV2026

TransNormal: Dense Visual Semantics for Diffusion-based Transparent Object Normal Estimation

Mingwei Li, Hehe Fan, Yi Yang

Monocular normal estimation for transparent objects is critical for laboratory automation, yet it remains challenging due to complex light refraction and reflection. These optical…

cs.CV2026

GraphTARIF: Linear Graph Transformer with Augmented Rank and Improved Focus

Zhaolin Hu, Kun Li, Hehe Fan +1

Linear attention mechanisms have emerged as efficient alternatives to full self-attention in Graph Transformers, offering linear time complexity. However, existing linear attention…