collaborators

7 papers

cs.CV2026

JointHOI: Jointly Generating Contact Maps Enhances Hand Object Interaction Generation

Mingyeong Song, Jungbin Cho, Jisoo Kim +5

Text driven hand object interaction (HOI) generation is gaining attention for immersive applications and robotics, yet producing physically plausible interactions remains challengi…

cs.RO2026

AutoDex: An Automated Real-World System for Dexterous Grasping Data Collection

Mingi Choi, Gunhee Kim, Jisoo Kim +4

Learning robust dexterous grasping requires real-world data that records the physical outcomes of grasp attempts. Such data is hard to obtain at scale: teleoperation yields valid p…

cs.RO2026

ZeroDex: Zero-Shot Long-Horizon Dexterous Manipulation via Multi-View 3D-Grounded VLM Reasoning

Jisoo Kim, Sangwon Baik, Taeksoo Kim +6

We present ZeroDex, a zero-shot framework for long-horizon dexterous manipulation that grounds language instructions into executable 3D task plans from calibrated multi-view RGB im…

cs.RO2026

OmniRobotHome: A Multi-Camera Home Platform for Real-Time Human-Robot Interaction

Junyoung Lee, Inhee Lee, Sookwan Han +9

Robots that assist people must respond promptly and appropriately to human activity, which requires low-latency processing, accurate perception, and anticipation of human motion. T…

cs.RO2026

HRDexDB: A 4D Dexterous Grasping Dataset Across Human and Multiple Robot Embodiments

Jongbin Lim, Taeyun Ha, Mingi Choi +6

We present HRDexDB, a real-world 4D dexterous grasping dataset capturing 3D hand-object interaction trajectories over time across five embodiments. The dataset comprises 3.2K trial…

cs.CV2026

Pri4R: Learning World Dynamics for Vision-Language-Action Models with Privileged 4D Representation

Jisoo Kim, Jungbin Cho, Sanghyeok Chu +9

Humans learn not only how their bodies move, but also how the surrounding world responds to their actions. In contrast, while recent Vision-Language-Action (VLA) models exhibit imp…

cs.RO2025

Learning to Transfer Human Hand Skills for Robot Manipulations

Sungjae Park, Seungho Lee, Mingi Choi +4

We present a method for teaching dexterous manipulation tasks to robots from human hand motion demonstrations. Unlike existing approaches that solely rely on kinematics information…