5 papers
BooST: Bridging Semantics and Motions for Efficient Skill Transfer
Jusuk Lee, Daesol Cho, Jonghun Shin +4
Skill abstraction---the process of learning reusable and temporally extended behaviors---has emerged as a key paradigm for improving sample efficiency and generalization in robot l…
ObsGraph: Hierarchical Observation Representation for Embodied Reasoning and Exploration
Taekbeom Lee, Youngseok Jang, Jeonghwa Heo +2
Embodied reasoning and exploration are increasingly considered crucial abilities for robots operating in complex and unfamiliar environments. To accomplish tasks in such settings,…
HERE: Hierarchical Active Exploration of Radiance Field with Epistemic Uncertainty Minimization
Taekbeom Lee, Dabin Kim, Youngseok Jang +1
We present HERE, an active 3D scene reconstruction framework based on neural radiance fields, enabling high-fidelity implicit mapping. Our approach centers around an active learnin…
Category-level Neural Field for Reconstruction of Partially Observed Objects in Indoor Environment
Taekbeom Lee, Youngseok Jang, H. Jin Kim
Neural implicit representation has attracted attention in 3D reconstruction through various success cases. For further applications such as scene understanding or editing, several…
Object Remover Performance Evaluation Methods using Class-wise Object Removal Images
Changsuk Oh, Dongseok Shim, Taekbeom Lee +1
Object removal refers to the process of erasing designated objects from an image while preserving the overall appearance, and it is one area where image inpainting is widely used i…