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20242026
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cs.CV2026

SimuScene: Simulation-Ready Compositional 3D Scene Reconstruction from a Single Image

Inhee Lee, Sangwon Baik, Sungjoo Kim +3

Reconstructing interactive, simulation-ready 3D scenes from a single image is a critical bottleneck for robotic manipulation. While recent single-image lifters recover plausible pe…

cs.CV2026

DeVI: Physics-based Dexterous Human-Object Interaction via Synthetic Video Imitation

Hyeonwoo Kim, Jeonghwan Kim, Kyungwon Cho +2

Physics-based character control for dexterous Human-Object Interaction (HOI) relies heavily on motion-capture data, which limits its applicability beyond captured scenarios. Meanwh…

cs.CV2025

Learning 3D Object Spatial Relationships from Pre-trained 2D Diffusion Models

Sangwon Baik, Hyeonwoo Kim, Hanbyul Joo

We present a method for learning 3D spatial relationships between object pairs, referred to as object-object spatial relationships (OOR), by leveraging synthetically generated 3D s…

cs.CV2025

DAViD: Modeling Dynamic Affordance of 3D Objects Using Pre-trained Video Diffusion Models

Hyeonwoo Kim, Sangwon Baik, Hanbyul Joo

Modeling how humans interact with objects is crucial for AI to effectively assist or mimic human behaviors. Existing studies for learning such ability primarily focus on static hum…

cs.CV2024

Beyond the Contact: Discovering Comprehensive Affordance for 3D Objects from Pre-trained 2D Diffusion Models

Hyeonwoo Kim, Sookwan Han, Patrick Kwon +1

Understanding the inherent human knowledge in interacting with a given environment (e.g., affordance) is essential for improving AI to better assist humans. While existing approach…