2 citations · 2 across the 11 of their papers we have counts for
11 papers
LoDA: A Level of Detection Aware Method and a Multimodal Sensing Benchmark for Object Level Change Detection
Haitian Wang, Xinyu Wang, Sheldon Fung +2
High-definition 3D LiDAR maps are important for autonomous driving and smart-city services, which require reliable detection of object-level changes in multi-temporal urban LiDAR t…
Disentangled Hierarchical VAE for 3D Human-Human Interaction Generation
Zichen Geng, Zeeshan Hayder, Bo Miao +3
Generating realistic 3D Human-Human Interaction (HHI) requires coherent modeling of the physical plausibility of the agents and their interaction semantics. Existing methods compre…
Statistical Verification of Medium-Access Parameterization for Power-Grid Edge Ad Hoc Sensor Networks
Haitian Wang, Xinyu Wang, Zichen Geng +3
The widespread deployment of power grid ad hoc sensor networks based on IEEE 802.15.4 raises reliability challenges when nodes selfishly adapt CSMA/CA parameters to maximize indivi…
ARMFlow: AutoRegressive MeanFlow for Online 3D Human Reaction Generation
Zichen Geng, Zeeshan Hayder, Wei Liu +2
3D human reaction generation faces three main challenges:(1) high motion fidelity, (2) real-time inference, and (3) autoregressive adaptability for online scenarios. Existing metho…
FLaTEC: Frequency-Disentangled Latent Triplanes for Efficient Compression of LiDAR Point Clouds
Xiaoge Zhang, Zijie Wu, Mingtao Feng +4
Point cloud compression methods jointly optimize bitrates and reconstruction distortion. However, balancing compression ratio and reconstruction quality is difficult because low-fr…
Quantization-Aware Neuromorphic Architecture for Skin Lesion Classification on Resource-Constrained Devices
Haitian Wang, Xia Cheng, Xinyu Wang +2
On-device skin lesion analysis is constrained by the compute and energy cost of conventional CNN inference and by the need for lightweight calibration under clinical data shift. Ne…
UniHM: Universal Human Motion Generation with Object Interactions in Indoor Scenes
Zichen Geng, Zeeshan Hayder, Wei Liu +1
Human motion synthesis in complex scenes presents a fundamental challenge, extending beyond conventional Text-to-Motion tasks by requiring the integration of diverse modalities suc…
MonoDiff9D: Monocular Category-Level 9D Object Pose Estimation via Diffusion Model
Jian Liu, Wei Sun, Hui Yang +4
Object pose estimation is a core means for robots to understand and interact with their environment. For this task, monocular category-level methods are attractive as they require…
Auto-Regressive Diffusion for Generating 3D Human-Object Interactions
Zichen Geng, Zeeshan Hayder, Wei Liu +1
Text-driven Human-Object Interaction (Text-to-HOI) generation is an emerging field with applications in animation, video games, virtual reality, and robotics. A key challenge in HO…
Calculation of the chiral Lagrangian coefficients with light vector mesons
Zi-Kan Geng, Qing Wang
We calculate the coefficients in the effective chiral Lagrangian from QCD, which includes pseudo-scalar mesons and vector mesons (with hidden symmetry), up to O(p4). This encompass…
Text-guided 3D Human Motion Generation with Keyframe-based Parallel Skip Transformer
Zichen Geng, Caren Han, Zeeshan Hayder +3
Text-driven human motion generation is an emerging task in animation and humanoid robot design. Existing algorithms directly generate the full sequence which is computationally exp…