118 citations · 222 across the 9 of their papers we have counts for
17 papers · 1 filter
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…
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…
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…
Self-Contrastive Learning with Hard Negative Sampling for Self-supervised Point Cloud Learning
Bi'an Du, Xiang Gao, Wei Hu +1
Point clouds have attracted increasing attention. Significant progress has been made in methods for point cloud analysis, which often requires costly human annotation as supervisio…
Diffusion Probabilistic Models for 3D Point Cloud Generation
Shitong Luo, Wei Hu
We present a probabilistic model for point cloud generation, which is fundamental for various 3D vision tasks such as shape completion, upsampling, synthesis and data augmentation.…
Self-Supervised Multi-View Learning via Auto-Encoding 3D Transformations
Xiang Gao, Wei Hu, Guo-Jun Qi
3D object representation learning is a fundamental challenge in computer vision to infer about the 3D world. Recent advances in deep learning have shown their efficiency in 3D obje…