Instance segmentation is a fundamental skill for many robotic applicatio...
Object recognition and instance segmentation are fundamental skills in a...
Predicting accurate depth with monocular images is important for low-cos...
We present an effective method for the matching of multimodal images.
Ac...
Particle dynamics and multi-agent systems provide accurate dynamical mod...
3D bounding boxes are a widespread intermediate representation in many
c...
The graph structure of road networks is critical for downstream tasks of...
With the rapid development of autonomous vehicles, there witnesses a boo...
In the presence of unmeasured confounders, we address the problem of
tre...
Machine learning models fail to perform well on real-world applications ...
Recent progress on parse tree encoder for sentence representation learni...
Road network graphs provide critical information for autonomous vehicle
...
Today's mainstream virtualization systems comprise of two cooperative
co...
High-Definition (HD) maps can provide precise geometric and semantic
inf...
Federated learning (FL) has emerged as an important machine learning par...
Object detection in 3D with stereo cameras is an important problem in
co...
Estimating the 3D position and orientation of objects in the environment...
In this paper, we introduce a novel suspect-and-investigate framework, w...
In this paper, we propose a novel model for time series prediction in wh...
Simulation can be a powerful tool for understanding machine learning sys...
In this work, we take a representation learning perspective on hierarchi...
Exploration is a fundamental challenge in reinforcement learning (RL). M...
Imitation learning is an effective approach for autonomous systems to ac...
Deep learning has made significant breakthroughs in various fields of
ar...