collaborators

5 papers

cs.CV2026

LTGS: Long-Term Gaussian Scene Chronology From Sparse View Updates

Minkwan Kim, Seungmin Lee, Junho Kim +1

Recent advances in novel-view synthesis can create the photo-realistic visualization of real-world environments from conventional camera captures. However, the everyday environment…

cs.RO2026

AnyCamVLA: Zero-Shot Camera Adaptation for Viewpoint Robust Vision-Language-Action Models

Hyeongjun Heo, Seungyeon Woo, Sang Min Kim +4

Despite remarkable progress in Vision-Language-Action models (VLAs) for robot manipulation, these large pre-trained models require fine-tuning to be deployed in specific environmen…

cs.RO2026

Point2Act: Efficient 3D Distillation of Multimodal LLMs for Zero-Shot Context-Aware Grasping

Sang Min Kim, Hyeongjun Heo, Junho Kim +2

We propose Point2Act, which directly retrieves the 3D action point relevant to a contextually described task, leveraging Multimodal Large Language Models (MLLMs). Foundation models…

cs.CV2025

Finding 3D Scene Analogies with Multimodal Foundation Models

Junho Kim, Young Min Kim

Connecting current observations with prior experiences helps robots adapt and plan in new, unseen 3D environments. Recently, 3D scene analogies have been proposed to connect two 3D…

cs.CV2025

Learning 3D Scene Analogies with Neural Contextual Scene Maps

Junho Kim, Gwangtak Bae, Eun Sun Lee +1

Understanding scene contexts is crucial for machines to perform tasks and adapt prior knowledge in unseen or noisy 3D environments. As data-driven learning is intractable to compre…