With the attention mechanism, transformers achieve significant empirical...
Recent progress on 2D object detection has featured Cascade RCNN, which
...
Outlier detection tasks have been playing a critical role in AI safety. ...
This paper presents an overview and comparative analysis of our systems
...
Reinforcement learning in partially observed Markov decision processes
(...
Despite the success of reinforcement learning (RL) for Markov decision
p...
Unsupervised learning is just at a tipping point where it could really t...
Visual navigation and three-dimensional (3D) scene reconstruction are
es...
Identifying feature correspondence between two images is a fundamental
p...
This paper explores useful modifications of the recent development in
co...
Recently, several direct processing point cloud models have achieved
sta...
Model-agnostic meta-learning (MAML) formulates meta-learning as a bileve...
Region sampling or weighting is significantly important to the success o...
Temporal-difference and Q-learning play a key role in deep reinforcement...
Generative adversarial imitation learning (GAIL) demonstrates tremendous...
While policy-based reinforcement learning (RL) achieves tremendous succe...
This notebook paper presents an overview and comparative analysis of our...
Policy gradient methods with actor-critic schemes demonstrate tremendous...
Proximal policy optimization and trust region policy optimization (PPO a...
This notebook paper presents an overview and comparative analysis of our...
This notebook paper presents an overview and comparative analysis of our...
Temporal-difference learning (TD), coupled with neural networks, is amon...
A general and fast method is conceived for computing the cyclic convolut...
Rendering synthetic data (e.g., 3D CAD-rendered images) to generate
anno...
We study the global convergence of generative adversarial imitation lear...
Two-view relative pose estimation and structure reconstruction is a clas...
Attitude computation is of vital importance for a variety of application...
In this paper, we introduce the new ideas of augmenting Convolutional Ne...