4 papers
SPACE-CLIP: Spatial Perception via Adaptive CLIP Embeddings for Monocular Depth Estimation
Taewan Cho, Taeryang Kim, Andrew Jaeyong Choi
Robotic and autonomous systems need dense spatial cues, but many monocular depth models are heavy, task-specific, or hard to attach to an existing multimodal stack. CLIP offers str…
Learning Multi-Stage Pick-and-Place with a Legged Mobile Manipulator
Haichao Zhang, Haonan Yu, Le Zhao +4
Quadruped-based mobile manipulation presents significant challenges in robotics due to the diversity of required skills, the extended task horizon, and partial observability. After…
SLIM: Sim-to-Real Legged Instructive Manipulation via Long-Horizon Visuomotor Learning
Haichao Zhang, Haonan Yu, Le Zhao +4
We present a low-cost legged mobile manipulation system that solves long-horizon real-world tasks, trained by reinforcement learning purely in simulation. This system is made possi…
Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation
Arvind Murari Vepa, Zukang Yang, Andrew Choi +3
Deep learning has seen remarkable advancements in machine learning, yet it often demands extensive annotated data. Tasks like 3D semantic segmentation impose a substantial annotati…