4 citations · 6 across the 15 of their papers we have counts for
18 papers
EgoRefine: Ego-Referenced Predictive Alignment and Trajectory-Conditioned Reliability-Aware Fusion for Asynchronous Collaborative Perception
Lingzhao Kong, Yongsheng Zang, Yu Kang +4
Collaborative perception enables connected agents to share complementary observations for 3D object detection, extending sensing range and mitigating occlusion. Under asynchronous…
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…
HGeo-TopoMap: Boosting Topological Mapping with Hierarchical Geometric Priors
Siyu Li, Kunyu Peng, Di Wen +3
Topological maps are key outputs of autonomous driving perception systems, delivering essential road information for path planning. They identify instances such as centerlines and…
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…
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…
CoBEVMoE: Heterogeneity-aware Feature Fusion with Dynamic Mixture-of-Experts for Collaborative Perception
Lingzhao Kong, Jiacheng Lin, Siyu Li +3
Collaborative perception aims to extend sensing coverage and improve perception accuracy by sharing information among multiple agents. However, due to differences in viewpoints and…
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…
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…
HierDAMap: Towards Universal Domain Adaptive BEV Mapping via Hierarchical Perspective Priors
Siyu Li, Yihong Cao, Hao Shi +4
The exploration of Bird's-Eye View (BEV) mapping technology has driven significant innovation in visual perception technology for autonomous driving. BEV mapping models need to be…
Resource-Efficient Affordance Grounding with Complementary Depth and Semantic Prompts
Yizhou Huang, Fan Yang, Guoliang Zhu +6
Affordance refers to the functional properties that an agent perceives and utilizes from its environment, and is key perceptual information required for robots to perform actions.…
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…
L2G-Map: Local-to-Global Mapping via Hierarchical Diffusion Refinement and Elliptical Bayesian Fusion
Siyu Li, Xinying Hong, Fei Teng +5
Offline high-definition maps provide essential geometric and topological priors for autonomous driving systems. Pure-vision solutions have become the predominant paradigm for offli…
GenMapping: Unleashing the Potential of Inverse Perspective Mapping for Robust Online HD Map Construction
Siyu Li, Kailun Yang, Hao Shi +3
Online High-Definition (HD) maps have emerged as the preferred option for autonomous driving, overshadowing the counterpart offline HD maps due to flexible update capability and lo…
DTCLMapper: Dual Temporal Consistent Learning for Vectorized HD Map Construction
Siyu Li, Jiacheng Lin, Hao Shi +5
Temporal information plays a pivotal role in Bird's-Eye-View (BEV) driving scene understanding, which can alleviate the visual information sparsity. However, the indiscriminate tem…
MambaMOS: LiDAR-based 3D Moving Object Segmentation with Motion-aware State Space Model
Kang Zeng, Hao Shi, Jiacheng Lin +5
LiDAR-based Moving Object Segmentation (MOS) aims to locate and segment moving objects in point clouds of the current scan using motion information from previous scans. Despite the…
EchoTrack: Auditory Referring Multi-Object Tracking for Autonomous Driving
Jiacheng Lin, Jiajun Chen, Kunyu Peng +4
This paper introduces the task of Auditory Referring Multi-Object Tracking (AR-MOT), which dynamically tracks specific objects in a video sequence based on audio expressions and ap…
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…