8 papers
Measurement Plasticity: Sensor-Level Adaptation for Vision-Language Models
Boyeong Im, Wooseok Lee, Yoojin Kwon +1
We propose Multi-View Physical-prompt (MVP) for Test-Time Adaptation (TTA), a forward-only framework that moves TTA from tokens to photons by treating the camera exposure triangle…
Back to the Familiar Future: Failure Recovery for VLA Policies via Pre-Imagined Milestone Selection
Suyeon Shin, Juwon Kim, Hyeonbin Park +4
Vision-language-action (VLA) policies can deviate from nominal trajectories during manipulation, even when tasks remain physically feasible. Recovering from these deviations is cha…
Adaptive Camera Sensor for Vision Models
Eunsu Baek, Sunghwan Han, Taesik Gong +1
Domain shift remains a persistent challenge in deep-learning-based computer vision, often requiring extensive model modifications or large labeled datasets to address. Inspired by…
EgoXtreme: A Dataset for Robust Object Pose Estimation in Egocentric Views under Extreme Conditions
Taegyoon Yoon, Yegyu Han, Seojin Ji +4
Smart glass is emerging as an useful device since it provides plenty of insights under hands-busy, eyes-on-task situations. To understand the context of the wearer, 6D object pose…
SenseShift6D: Multimodal RGB-D Benchmarking for Robust 6D Pose Estimation across Environment and Sensor Variations
Yegyu Han, Taegyoon Yoon, Dayeon Woo +2
Recent advances on 6D object pose estimation have achieved high performance on representative benchmarks such as LM-O, YCB-V, and T-Less. However, these datasets were captured unde…
AI Should Sense Better, Not Just Scale Bigger: Adaptive Sensing as a Paradigm Shift
Eunsu Baek, Keondo Park, Jeonggil Ko +3
Current AI advances largely rely on scaling neural models and expanding training datasets to achieve generalization and robustness. Despite notable successes, this paradigm incurs…