5 papers · 1 filter
GeoWAM: Visual Geometry World Action Models for Autonomous Driving
Yiren Lu, Xin Ye, Jiaming Liu +10
World action models (WAMs) have recently gained increasing attention as a framework for jointly modeling scene evolution and ego actions in autonomous driving. Most existing WAMs l…
TraVEL: Trajectory-Guided Video Embedding Learning for Driving-Video Retrieval
Yi-Chung Chen, Philip Jacobson, Tom Lampo +6
Efficiently retrieving relevant clips from large-scale driving logs is essential for data curation, model development, and safety analysis. Structured and rule-based retrieval syst…
VLGA: Vision-Language-Geometry-Action Models for Autonomous Driving
Jin Yao, Dhruva Dixith Kurra, Tom Lampo +3
Vision-language-action (VLA) models can describe scenes and reason about them in language, yet still struggle to ground their actions in the dense 3D world around them. Existing ap…
LabelAny3D: Label Any Object 3D in the Wild
Jin Yao, Radowan Mahmud Redoy, Sebastian Elbaum +2
Detecting objects in 3D space from monocular input is crucial for applications ranging from robotics to scene understanding. Despite advanced performance in the indoor and autonomo…
Open Vocabulary Monocular 3D Object Detection
Jin Yao, Hao Gu, Xuweiyi Chen +2
We propose and study open-vocabulary monocular 3D detection, a novel task that aims to detect objects of any categores in metric 3D space from a single RGB image. Existing 3D objec…