7 papers
SECOND-Grasp: Semantic Contact-guided Dexterous Grasping
Han Yi Shin, Heeju Ko, Jaewon Mun +6
Achieving reliable robotic manipulation, such as dexterous grasping, requires a synergy between physically stable interactions and semantic task guidance, yet these objectives are…
DAM-VLA: A Dynamic Action Model-Based Vision-Language-Action Framework for Robot Manipulation
Xiongfeng Peng, Jiaqian Yu, Dingzhe Li +8
In dynamic environments such as warehouses, hospitals, and homes, robots must seamlessly transition between gross motion and precise manipulations to complete complex tasks. Howeve…
RevoNAD: Reflective Evolutionary Exploration for Neural Architecture Design
Gyusam Chang, Jeongyoon Yoon, Shin han yi +3
Recent progress in leveraging large language models (LLMs) has enabled Neural Architecture Design (NAD) systems to generate new architecture not limited from manually predefined se…
Active Test-time Vision-Language Navigation
Heeju Ko, Sungjune Kim, Gyeongrok Oh +5
Vision-Language Navigation (VLN) policies trained on offline datasets often exhibit degraded task performance when deployed in unfamiliar navigation environments at test time, wher…
3D Occupancy Prediction with Low-Resolution Queries via Prototype-aware View Transformation
Gyeongrok Oh, Sungjune Kim, Heeju Ko +7
The resolution of voxel queries significantly influences the quality of view transformation in camera-based 3D occupancy prediction. However, computational constraints and the prac…
Unveiling the Hidden: Online Vectorized HD Map Construction with Clip-Level Token Interaction and Propagation
Nayeon Kim, Hongje Seong, Daehyun Ji +1
Predicting and constructing road geometric information (e.g., lane lines, road markers) is a crucial task for safe autonomous driving, while such static map elements can be repeate…