11 citations · 51 across the 36 of their papers we have counts for
37 papers
FlowMAS: Learning Multi-Agent Workflow Topology via Information-guided Generative Flow Network
Haitao Wang, Chenjing Liang, Haipeng Zhang +6
Automated multi-agent systems offer clear advantages over manually designed ones in scalability and adaptability, but existing workflow topology methods still face important limita…
MotionMAR: Multi-scale Auto-Regressive Human Motion Reconstruction from Sparse Observations
Yuhua Luo, Junsheng Zhang, Mengyin Liu +7
Human motion follows a temporal hierarchical structure, transitioning from low-frequency global trajectories to high-frequency details. Inspired by the success of multi-level autor…
LEADER: Learning Reliable Local-to-Global Correspondences for LiDAR Relocalization
Jianshi Wu, Minghang Zhu, Dunqiang Liu +5
LiDAR relocalization has attracted increasing attention as it can deliver accurate 6-DoF pose estimation in complex 3D environments. Recent learning-based regression methods offer…
V2U4Real: A Real-world Large-scale Dataset for Vehicle-to-UAV Cooperative Perception
Weijia Li, Haoen Xiang, Tianxu Wang +4
Modern autonomous vehicle perception systems are often constrained by occlusions, blind spots, and limited sensing range. While existing cooperative perception paradigms, such as V…
FlashCap: Millisecond-Accurate Human Motion Capture via Flashing LEDs and Event-Based Vision
Zekai Wu, Shuqi Fan, Mengyin Liu +10
Precise motion timing (PMT) is crucial for swift motion analysis. A millisecond difference may determine victory or defeat in sports competitions. Despite substantial progress in h…
AW-MoE: All-Weather Mixture of Experts for Robust Multi-Modal 3D Object Detection
Hongwei Lin, Xun Huang, Chenglu Wen +1
Robust 3D object detection under adverse weather conditions is crucial for autonomous driving. However, most existing methods simply combine all weather samples for training while…
Towards Motion Turing Test: Evaluating Human-Likeness in Humanoid Robots
Mingzhe Li, Mengyin Liu, Zekai Wu +9
Humanoid robots have achieved significant progress in motion generation and control, exhibiting movements that appear increasingly natural and human-like. Inspired by the Turing Te…
MAGE: Multi-scale Autoregressive Generation for Offline Reinforcement Learning
Chenxing Lin, Xinhui Gao, Haipeng Zhang +7
Generative models have gained significant traction in offline reinforcement learning (RL) due to their ability to model complex trajectory distributions. However, existing generati…
SOAR: Regression-based LiDAR Relocalization for UAVs
Hengyu Mu, Jianshi Wu, Yuxin Guo +5
Regression-based LiDAR relocalization has recently emerged as a promising solution for high-precision positioning in GNSS-denied environments. However, these methods are primarily…
MoniRefer: A Real-world Large-scale Multi-modal Dataset based on Roadside Infrastructure for 3D Visual Grounding
Panquan Yang, Junfei Huang, Zongzhangbao Yin +9
3D visual grounding aims to localize the object in 3D point cloud scenes that semantically corresponds to given natural language sentences. It is very critical for roadside infrast…
ClimbingCap: Multi-Modal Dataset and Method for Rock Climbing in World Coordinate
Ming Yan, Xincheng Lin, Yuhua Luo +9
Human Motion Recovery (HMR) research mainly focuses on ground-based motions such as running. The study on capturing climbing motion, an off-ground motion, is sparse. This is partly…
LightLoc: Learning Outdoor LiDAR Localization at Light Speed
Wen Li, Chen Liu, Shangshu Yu +5
Scene coordinate regression achieves impressive results in outdoor LiDAR localization but requires days of training. Since training needs to be repeated for each new scene, long tr…
Seg2Box: 3D Object Detection by Point-Wise Semantics Supervision
Maoji Zheng, Ziyu Xu, Qiming Xia +3
LiDAR-based 3D object detection and semantic segmentation are critical tasks in 3D scene understanding. Traditional detection and segmentation methods supervise their models throug…
Learning to Detect Objects from Multi-Agent LiDAR Scans without Manual Labels
Qiming Xia, Wenkai Lin, Haoen Xiang +5
Unsupervised 3D object detection serves as an important solution for offline 3D object annotation. However, due to the data sparsity and limited views, the clustering-based label f…
SP3D: Boosting Sparsely-Supervised 3D Object Detection via Accurate Cross-Modal Semantic Prompts
Shijia Zhao, Qiming Xia, Xusheng Guo +5
Recently, sparsely-supervised 3D object detection has gained great attention, achieving performance close to fully-supervised 3D objectors while requiring only a few annotated inst…
Mining and Transferring Feature-Geometry Coherence for Unsupervised Point Cloud Registration
Kezheng Xiong, Haoen Xiang, Qingshan Xu +4
Point cloud registration, a fundamental task in 3D vision, has achieved remarkable success with learning-based methods in outdoor environments. Unsupervised outdoor point cloud reg…
Federated Graph Learning for Cross-Domain Recommendation
Ziqi Yang, Zhaopeng Peng, Zihui Wang +6
Cross-domain recommendation (CDR) offers a promising solution to the data sparsity problem by enabling knowledge transfer across source and target domains. However, many recent CDR…
V2X-R: Cooperative LiDAR-4D Radar Fusion with Denoising Diffusion for 3D Object Detection
Xun Huang, Jinlong Wang, Qiming Xia +5
Current Vehicle-to-Everything (V2X) systems have significantly enhanced 3D object detection using LiDAR and camera data. However, these methods suffer from performance degradation…
HiSC4D: Human-centered interaction and 4D Scene Capture in Large-scale Space Using Wearable IMUs and LiDAR
Yudi Dai, Zhiyong Wang, Xiping Lin +5
We introduce HiSC4D, a novel Human-centered interaction and 4D Scene Capture method, aimed at accurately and efficiently creating a dynamic digital world, containing large-scale in…
SC3D: Label-Efficient Outdoor 3D Object Detection via Single Click Annotation
Qiming Xia, Hongwei Lin, Wei Ye +4
LiDAR-based outdoor 3D object detection has received widespread attention. However, training 3D detectors from the LiDAR point cloud typically relies on expensive bounding box anno…
L4DR: LiDAR-4DRadar Fusion for Weather-Robust 3D Object Detection
Xun Huang, Ziyu Xu, Hai Wu +7
LiDAR-based vision systems are integral for 3D object detection, which is crucial for autonomous navigation. However, they suffer from performance degradation in adverse weather co…
FedSAC: Dynamic Submodel Allocation for Collaborative Fairness in Federated Learning
Zihui Wang, Zheng Wang, Lingjuan Lyu +6
Collaborative fairness stands as an essential element in federated learning to encourage client participation by equitably distributing rewards based on individual contributions. E…
FedPFT: Federated Proxy Fine-Tuning of Foundation Models
Zhaopeng Peng, Xiaoliang Fan, Yufan Chen +5
Adapting Foundation Models (FMs) for downstream tasks through Federated Learning (FL) emerges a promising strategy for protecting data privacy and valuable FMs. Existing methods fi…
Commonsense Prototype for Outdoor Unsupervised 3D Object Detection
Hai Wu, Shijia Zhao, Xun Huang +3
The prevalent approaches of unsupervised 3D object detection follow cluster-based pseudo-label generation and iterative self-training processes. However, the challenge arises due t…