12 papers
mmSimPrior: Learning Simulation Priors for Data-Efficient and Generalizable Real-World Radar-based Human Motion Reconstruction
Cheng Guo, Qiming Cao, Shengkai Xu +4
Millimeter-wave (mmWave) radar enables privacy-preserving and illumination-robust human motion reconstruction, but training generalizable models typically requires costly paired ra…
HybridSim: A Physics-Learning Hybrid Digital Twin for mmWave Human Sensing
Weitao Xiong, Tianyu Liu, Peng Li +4
High-fidelity simulation of mmWave radar signals for dynamic human motion is valuable for developing radar-based human sensing models; yet collecting accurately labeled measurement…
CLLAP: Contrastive Learning-based LiDAR-Augmented Pretraining for Enhanced Radar-Camera Fusion
Bingyi Liu, Chuanhui Zhu, Hongfei Xue +5
Accurate 3D object detection is critical for autonomous driving, necessitating reliable, cost-effective sensors capable of operating in adverse weather conditions. Camera and milli…
Monocular Models are Strong Learners for Multi-View Human Mesh Recovery
Haoyu Xie, Shengkai Xu, Cheng Guo +6
Multi-view human mesh recovery (HMR) is broadly deployed in diverse domains where high accuracy and strong generalization are essential. Existing approaches can be broadly grouped…
Send Less, Perceive More: Masked Quantized Point Cloud Communication for Loss-Tolerant Collaborative Perception
Sheng Xu, Enshu Wang, Hongfei Xue +6
Collaborative perception allows connected vehicles to overcome occlusions and limited viewpoints by sharing sensory information. However, existing approaches struggle to achieve hi…
MonoMSK: Monocular 3D Musculoskeletal Dynamics Estimation
Farnoosh Koleini, Hongfei Xue, Ahmed Helmy +1
Reconstructing biomechanically realistic 3D human motion - recovering both kinematics (motion) and kinetics (forces) - is a critical challenge. While marker-based systems are lab-b…
Walk Before You Dance: High-fidelity and Editable Dance Synthesis via Generative Masked Motion Prior
Foram N Shah, Parshwa Shah, Muhammad Usama Saleem +4
Recent advances in dance generation have enabled the automatic synthesis of 3D dance motions. However, existing methods still face significant challenges in simultaneously achievin…
BioPose: Biomechanically-accurate 3D Pose Estimation from Monocular Videos
Farnoosh Koleini, Muhammad Usama Saleem, Pu Wang +3
Recent advancements in 3D human pose estimation from single-camera images and videos have relied on parametric models, like SMPL. However, these models oversimplify anatomical stru…
mmCooper: A Multi-agent Multi-stage Communication-efficient and Collaboration-robust Cooperative Perception Framework
Bingyi Liu, Jian Teng, Hongfei Xue +4
Collaborative perception significantly enhances individual vehicle perception performance through the exchange of sensory information among agents. However, real-world deployment f…
GenHMR: Generative Human Mesh Recovery
Muhammad Usama Saleem, Ekkasit Pinyoanuntapong, Pu Wang +3
Human mesh recovery (HMR) is crucial in many computer vision applications; from health to arts and entertainment. HMR from monocular images has predominantly been addressed by dete…
MaskHand: Generative Masked Modeling for Robust Hand Mesh Reconstruction in the Wild
Muhammad Usama Saleem, Ekkasit Pinyoanuntapong, Mayur Jagdishbhai Patel +4
Reconstructing a 3D hand mesh from a single RGB image is challenging due to complex articulations, self-occlusions, and depth ambiguities. Traditional discriminative methods, which…
MaskControl: Spatio-Temporal Control for Masked Motion Synthesis
Ekkasit Pinyoanuntapong, Muhammad Usama Saleem, Korrawe Karunratanakul +7
Recent advances in motion diffusion models have enabled spatially controllable text-to-motion generation. However, these models struggle to achieve high-precision control while mai…