65 citations · 233 across the 23 of their papers we have counts for
7 papers · 1 filter
PanoNet3D: Combining Semantic and Geometric Understanding for LiDARPoint Cloud Detection
Xia Chen, Jianren Wang, David Held +1
Visual data in autonomous driving perception, such as camera image and LiDAR point cloud, can be interpreted as a mixture of two aspects: semantic feature and geometric structure.…
Constrained Model-based Reinforcement Learning with Robust Cross-Entropy Method
Zuxin Liu, Hongyi Zhou, Baiming Chen +3
This paper studies the constrained/safe reinforcement learning (RL) problem with sparse indicator signals for constraint violations. We propose a model-based approach to enable RL…
Few-Shot Learning with Intra-Class Knowledge Transfer
Vivek Roy, Yan Xu, Yu-Xiong Wang +3
We consider the few-shot classification task with an unbalanced dataset, in which some classes have sufficient training samples while other classes only have limited training sampl…
Bowtie Networks: Generative Modeling for Joint Few-Shot Recognition and Novel-View Synthesis
Zhipeng Bao, Yu-Xiong Wang, Martial Hebert
We propose a novel task of joint few-shot recognition and novel-view synthesis: given only one or few images of a novel object from arbitrary views with only category annotation, w…
PanoNet: Real-time Panoptic Segmentation through Position-Sensitive Feature Embedding
Xia Chen, Jianren Wang, Martial Hebert
We propose a simple, fast, and flexible framework to generate simultaneously semantic and instance masks for panoptic segmentation. Our method, called PanoNet, incorporates a clean…
MAPPER: Multi-Agent Path Planning with Evolutionary Reinforcement Learning in Mixed Dynamic Environments
Zuxin Liu, Baiming Chen, Hongyi Zhou +3
Multi-agent navigation in dynamic environments is of great industrial value when deploying a large scale fleet of robot to real-world applications. This paper proposes a decentrali…