224 citations · 360 across the 4 of their papers we have counts for
8 papers
Learning Semantic Segmentation of Large-Scale Point Clouds with Random Sampling
Qingyong Hu, Bo Yang, Linhai Xie +5
We study the problem of efficient semantic segmentation of large-scale 3D point clouds. By relying on expensive sampling techniques or computationally heavy pre/post-processing ste…
Watch and Learn: Mapping Language and Noisy Real-world Videos with Self-supervision
Yujie Zhong, Linhai Xie, Sen Wang +2
In this paper, we teach machines to understand visuals and natural language by learning the mapping between sentences and noisy video snippets without explicit annotations. Firstly…
RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds
Qingyong Hu, Bo Yang, Linhai Xie +5
We study the problem of efficient semantic segmentation for large-scale 3D point clouds. By relying on expensive sampling techniques or computationally heavy pre/post-processing st…
Learning with Training Wheels: Speeding up Training with a Simple Controller for Deep Reinforcement Learning
Linhai Xie, Sen Wang, Stefano Rosa +2
Deep Reinforcement Learning (DRL) has been applied successfully to many robotic applications. However, the large number of trials needed for training is a key issue. Most of existi…
Learning with Stochastic Guidance for Navigation
Linhai Xie, Yishu Miao, Sen Wang +5
Due to the sparse rewards and high degree of environment variation, reinforcement learning approaches such as Deep Deterministic Policy Gradient (DDPG) are plagued by issues of hig…
Neural Allocentric Intuitive Physics Prediction from Real Videos
Zhihua Wang, Stefano Rosa, Yishu Miao +4
Humans are able to make rich predictions about the future dynamics of physical objects from a glance. On the other hand, most existing computer vision approaches require strong ass…