5 papers
SpaCeFormer: Fast Proposal-Free Open-Vocabulary 3D Instance Segmentation
Chris Choy, Junha Lee, Chunghyun Park +2
Open-vocabulary 3D instance segmentation is a core capability for robotics and AR/VR, but prior methods trade one bottleneck for another: multi-stage 2D+3D pipelines aggregate foun…
DextER: Language-driven Dexterous Grasp Generation with Embodied Reasoning
Junha Lee, Eunha Park, Minsu Cho
Language-driven dexterous grasp generation requires the models to understand task semantics, 3D geometry, and complex hand-object interactions. While vision-language models have be…
Affogato: Open-Vocabulary Affordance Grounding with Automated Data Generation at Scale
Junha Lee, Eunha Park, Chunghyun Park +2
Affordance grounding aims to localize where to interact with an object, a fundamental capability for embodied agents. Yet progress is bottlenecked by data: manual annotation is pro…
Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation
Junha Lee, Chunghyun Park, Jaesung Choe +4
We tackle open-vocabulary 3D scene understanding by introducing a novel data generation pipeline and training framework. Our method addresses three critical requirements for effect…
3D Geometric Shape Assembly via Efficient Point Cloud Matching
Nahyuk Lee, Juhong Min, Junha Lee +4
Learning to assemble geometric shapes into a larger target structure is a pivotal task in various practical applications. In this work, we tackle this problem by establishing local…