6 papers
CoHuB: A Simulation Benchmark for Multi-Humanoid Collaboration
Hyunjin Park, Jebeom Chae, Minwoo Park +11
Many physical tasks in human environments require collaboration, from assisting a partner to jointly manipulating an object. Yet, existing humanoid benchmarks largely focus on sing…
Symmetry-Aware Steering of Equivariant Diffusion Policies: Benefits and Limits
Minwoo Park, Junwoo Chang, Jongeun Choi +1
Equivariant diffusion policies (EDPs) combine the generative expressivity of diffusion models with the strong generalization and sample efficiency afforded by geometric symmetries.…
Scale-invariant and View-relational Representation Learning for Full Surround Monocular Depth
Kyumin Hwang, Wonhyeok Choi, Kiljoon Han +5
Recent foundation models demonstrate strong generalization capabilities in monocular depth estimation. However, directly applying these models to Full Surround Monocular Depth Esti…
Partially Equivariant Reinforcement Learning in Symmetry-Breaking Environments
Junwoo Chang, Minwoo Park, Joohwan Seo +3
Group symmetries provide a powerful inductive bias for reinforcement learning (RL), enabling efficient generalization across symmetric states and actions via group-invariant Markov…
Augmented Reality based Simulated Data (ARSim) with multi-view consistency for AV perception networks
Aqeel Anwar, Tae Eun Choe, Zian Wang +2
Detecting a diverse range of objects under various driving scenarios is essential for the effectiveness of autonomous driving systems. However, the real-world data collected often…
NVAutoNet: Fast and Accurate 360 3D Visual Perception For Self Driving
Trung Pham, Mehran Maghoumi, Wanli Jiang +9
Achieving robust and real-time 3D perception is fundamental for autonomous vehicles. While most existing 3D perception methods prioritize detection accuracy, they often overlook cr…