195 citations · 787 across the 32 of their papers we have counts for
32 papers
Learning Latent Part-Whole Hierarchies for Point Clouds
Xiang Gao, Wei Hu, Renjie Liao
Strong evidence suggests that humans perceive the 3D world by parsing visual scenes and objects into part-whole hierarchies. Although deep neural networks have the capability of le…
Neural Capture of Animatable 3D Human from Monocular Video
Gusi Te, Xiu Li, Xiao Li +3
We present a novel paradigm of building an animatable 3D human representation from a monocular video input, such that it can be rendered in any unseen poses and views. Our method i…
Point Cloud Attacks in Graph Spectral Domain: When 3D Geometry Meets Graph Signal Processing
Daizong Liu, Wei Hu, Xin Li
With the increasing attention in various 3D safety-critical applications, point cloud learning models have been shown to be vulnerable to adversarial attacks. Although existing 3D…
Exploring Optical-Flow-Guided Motion and Detection-Based Appearance for Temporal Sentence Grounding
Daizong Liu, Xiang Fang, Wei Hu +1
Temporal sentence grounding aims to localize a target segment in an untrimmed video semantically according to a given sentence query. Most previous works focus on learning frame-le…
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…
Deep Point Set Resampling via Gradient Fields
Haolan Chen, Bi'an Du, Shitong Luo +1
3D point clouds acquired by scanning real-world objects or scenes have found a wide range of applications including immersive telepresence, autonomous driving, surveillance, etc. T…