7 papers
EmbPASS: Towards Cross-Embodiment Open Panoramic Segmentation
Pujun Guo, Yuanfan Zheng, Fei Teng +5
Panoramic images provide a complete 360-degree field of view, enabling comprehensive scene understanding for embodied perception. However, heterogeneous embodied platforms exhibit…
OmniAct3D: Leveraging Foundation Geometry and Evidence-Grounded Reasoning for Panoramic 3D Detection
Runtong Wu, Fei Teng, Di Wen +3
Accurate 3D detection is essential for mobile embodied agents, while Vision Foundation Models (VFMs) offer transferable visual and geometric priors. Yet existing VFM-based 3D detec…
OmniMimic: Dynamics-completed Motion Augmentation for Multi-style Omnidirectional Quadruped Locomotion
Sheng Wu, Guoqiang Zhao, Zhe Yang +7
Animal demonstrations provide quadruped robots with natural and distinctive gait styles that are difficult to specify through hand-crafted rewards. However, their narrow directiona…
Spheriverse: 3D Scene Understanding from Spherical Observations in the Wild
Fei Teng, Sheng Wu, Mengfei Duan +7
Spherical observations provide global visual context for 3D scene understanding. However, visual information is encoded in an angular domain, whereas the physical world is represen…
Panoramic Multimodal Semantic Occupancy Prediction for Quadruped Robots
Guoqiang Zhao, Zhe Yang, Sheng Wu +5
Panoramic imagery provides holistic 360° visual coverage for environmental perception in quadruped robots. However, existing occupancy prediction methods are primarily designed for…
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…
Unveiling the Potential of Segment Anything Model 2 for RGB-Thermal Semantic Segmentation with Language Guidance
Jiayi Zhao, Fei Teng, Kai Luo +4
The perception capability of robotic systems relies on the richness of the dataset. Although Segment Anything Model 2 (SAM2), trained on large datasets, demonstrates strong percept…