36 citations · 53 across the 7 of their papers we have counts for
7 papers
RangeLDM: Fast Realistic LiDAR Point Cloud Generation
Qianjiang Hu, Zhimin Zhang, Wei Hu
Autonomous driving demands high-quality LiDAR data, yet the cost of physical LiDAR sensors presents a significant scaling-up challenge. While recent efforts have explored deep gene…
Density-Insensitive Unsupervised Domain Adaption on 3D Object Detection
Qianjiang Hu, Daizong Liu, Wei Hu
3D object detection from point clouds is crucial in safety-critical autonomous driving. Although many works have made great efforts and achieved significant progress on this task,…
Dynamic Point Cloud Denoising via Gradient Fields
Qianjiang Hu, Wei Hu
3D dynamic point clouds provide a discrete representation of real-world objects or scenes in motion, which have been widely applied in immersive telepresence, autonomous driving, s…
Exploring the Devil in Graph Spectral Domain for 3D Point Cloud Attacks
Qianjiang Hu, Daizong Liu, Wei Hu
With the maturity of depth sensors, point clouds have received increasing attention in various applications such as autonomous driving, robotics, surveillance, etc., while deep poi…
AdCo: Adversarial Contrast for Efficient Learning of Unsupervised Representations from Self-Trained Negative Adversaries
Qianjiang Hu, Xiao Wang, Wei Hu +1
Contrastive learning relies on constructing a collection of negative examples that are sufficiently hard to discriminate against positive queries when their representations are sel…
Dynamic Point Cloud Denoising via Manifold-to-Manifold Distance
Wei Hu, Qianjiang Hu, Zehua Wang +1
3D dynamic point clouds provide a natural discrete representation of real-world objects or scenes in motion, with a wide range of applications in immersive telepresence, autonomous…
3D Dynamic Point Cloud Denoising via Spatial-Temporal Graph Learning
Wei Hu, Qianjiang Hu, Zehua Wang +1
The prevalence of accessible depth sensing and 3D laser scanning techniques has enabled the convenient acquisition of 3D dynamic point clouds, which provide efficient representatio…