7 papers
ProOOD: Prototype-Guided Out-of-Distribution 3D Occupancy Prediction
Yuheng Zhang, Mengfei Duan, Kunyu Peng +5
3D semantic occupancy prediction is central to autonomous driving, yet current methods are vulnerable to long-tailed class bias and out-of-distribution (OOD) inputs, often overconf…
O3N: Omnidirectional Open-Vocabulary Occupancy Prediction for Embodied Intelligent Robotics
Mengfei Duan, Hao Shi, Fei Teng +4
The rapid evolution of consumer electronics toward embodied intelligence has accelerated the emergence of Consumer Embodied Intelligent Robotics (CEIRs), where intelligent devices…
PanoAffordanceNet: Towards Holistic Affordance Grounding in 360° Indoor Environments
Guoliang Zhu, Wanjun Jia, Caoyang Shao +3
Global perception is essential for embodied agents in 360° spaces, yet current affordance grounding remains largely object-centric and restricted to perspective views. To bridge th…
What if? Emulative Simulation with World Models for Situated Reasoning
Ruiping Liu, Yufan Chen, Yuheng Zhang +8
Situated reasoning often relies on active exploration, yet in many real-world scenarios such exploration is infeasible due to physical constraints of robots or safety concerns of v…
Can we Trust Unreliable Voxels? Exploring 3D Semantic Occupancy Prediction under Label Noise
Wenxin Li, Kunyu Peng, Di Wen +6
3D semantic occupancy prediction is a cornerstone of robotic perception, yet real-world voxel annotations are inherently corrupted by structural artifacts and dynamic trailing effe…
Out-of-Distribution Semantic Occupancy Prediction
Yuheng Zhang, Mengfei Duan, Kunyu Peng +6
3D semantic occupancy prediction is crucial for autonomous driving, providing a dense, semantically rich environmental representation. However, existing methods focus on in-distrib…