4 citations · 5 across the 16 of their papers we have counts for
21 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…
HEIR: Learning Human-Entity Interactions with Functional Roles
Di Wen, Wenhao Guo, Yuedong Tan +15
Understanding human-entity interactions requires recovering each person-action event's participants, roles, and shared identities. This structure can support embodied agents by cla…
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…
PS-MOT: Cultivating Instance Awareness from Point Seeds for Multi-Object Tracking
Kai Luo, Fei Teng, Mengfei Duan +6
We introduce Point-supervised Multi-Object Tracking (PS-MOT) as a cost-effective alternative to traditional bounding box supervision, shifting the focus from spatial fitting to top…
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…
OmniTrack++: Omnidirectional Multi-Object Tracking by Learning Large-FoV Trajectory Feedback
Kai Luo, Hao Shi, Kunyu Peng +4
To address panoramic distortion, large search space, and identity ambiguity under a 360° FoV, OmniTrack++ adopts a feedback-driven framework that progressively refines perception w…
DepTR-MOT: Unveiling the Potential of Depth-Informed Trajectory Refinement for Multi-Object Tracking
Buyin Deng, Lingxin Huang, Kai Luo +2
Visual Multi-Object Tracking (MOT) is a crucial component of robotic perception, yet existing Tracking-By-Detection (TBD) methods often rely on 2D cues, such as bounding boxes and…
Visually Grounded Narratives: Reducing Cognitive Burden in Researcher-Participant Interaction
Runtong Wu, Jiayao Song, Fei Teng +3
Narrative inquiry has been one of the prominent application domains for the analysis of human experience, aiming to know more about the complexity of human society. However, resear…
QuaDreamer: Controllable Panoramic Video Generation for Quadruped Robots
Sheng Wu, Fei Teng, Hao Shi +4
Panoramic cameras, capturing comprehensive 360-degree environmental data, are suitable for quadruped robots in surrounding perception and interaction with complex environments. How…
Hallucinating 360°: Panoramic Street-View Generation via Local Scenes Diffusion and Probabilistic Prompting
Fei Teng, Kai Luo, Sheng Wu +6
Panoramic perception holds significant potential for autonomous driving, enabling vehicles to acquire a comprehensive 360° surround view in a single shot. However, autonomous drivi…
NRSeg: Noise-Resilient Learning for BEV Semantic Segmentation via Driving World Models
Siyu Li, Fei Teng, Yihong Cao +3
Birds' Eye View (BEV) semantic segmentation is an indispensable perception task in end-to-end autonomous driving systems. Unsupervised and semi-supervised learning for BEV tasks, a…
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…
Go Beyond Earth: Understanding Human Actions and Scenes in Microgravity Environments
Di Wen, Lei Qi, Kunyu Peng +9
Despite substantial progress in video understanding, most existing datasets are limited to Earth's gravitational conditions. However, microgravity alters human motion, interactions…
Panoramic Out-of-Distribution Segmentation
Mengfei Duan, Yuheng Zhang, Yihong Cao +5
Panoramic imaging enables capturing 360° images with an ultra-wide Field-of-View (FoV) for dense omnidirectional perception, which is critical to applications such as autonomous dr…
Omnidirectional Multi-Object Tracking
Kai Luo, Hao Shi, Sheng Wu +6
Panoramic imagery, with its 360° field of view, offers comprehensive information to support Multi-Object Tracking (MOT) in capturing spatial and temporal relationships of surroundi…
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…
LFX: Towards Unified Light Field Dense Semantic Segmentation and Salient Object Detection
Fei Teng, Lingxin Huang, Buyin Deng +8
Light field cameras capture multi-view observations within a single exposure. However, existing studies are typically tailored to specific LF representations, leaving the field wit…
LF Tracy: A Unified Single-Pipeline Approach for Salient Object Detection in Light Field Cameras
Fei Teng, Jiaming Zhang, Jiawei Liu +4
Leveraging rich information is crucial for dense prediction tasks. Light field (LF) cameras are instrumental in this regard, as they allow data to be sampled from various perspecti…