Browse > Computer Vision > Autonomous Vehicles

Autonomous Vehicles

71 papers with code ยท Computer Vision

Autonomous vehicles is the task of making a vehicle that can guide itself without human conduction.

Many of the state-of-the-art results can be found at more general task pages such as 3D Object Detection and Semantic Segmentation.

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Latest papers without code

Spatiotemporal Relationship Reasoning for Pedestrian Intent Prediction

20 Feb 2020

In addition, we introduce a new dataset designed specifically for autonomous-driving scenarios in areas with dense pedestrian populations: the Stanford-TRI Intent Prediction (STIP) dataset.

AUTONOMOUS DRIVING

siaNMS: Non-Maximum Suppression with Siamese Networks for Multi-Camera 3D Object Detection

19 Feb 2020

The rapid development of embedded hardware in autonomous vehicles broadens their computational capabilities, thus bringing the possibility to mount more complete sensor setups able to handle driving scenarios of higher complexity.

3D OBJECT DETECTION AUTONOMOUS VEHICLES

Cooperative LIDAR Object Detection via Feature Sharing in Deep Networks

19 Feb 2020

The recent advancements in communication and computational systems has led to significant improvement of situational awareness in connected and autonomous vehicles.

AUTONOMOUS VEHICLES OBJECT DETECTION

Social-WaGDAT: Interaction-aware Trajectory Prediction via Wasserstein Graph Double-Attention Network

14 Feb 2020

Effective understanding of the environment and accurate trajectory prediction of surrounding dynamic obstacles are indispensable for intelligent mobile systems (like autonomous vehicles and social robots) to achieve safe and high-quality planning when they navigate in highly interactive and crowded scenarios.

AUTONOMOUS VEHICLES RELATIONAL REASONING TRAJECTORY PREDICTION

Improving Generalization of Reinforcement Learning with Minimax Distributional Soft Actor-Critic

13 Feb 2020

In this paper, we introduce the minimax formulation and distributional framework to improve the generalization ability of RL algorithms and develop the Minimax Distributional Soft Actor-Critic (Minimax DSAC) algorithm.

AUTONOMOUS DRIVING DECISION MAKING

Self-explaining AI as an alternative to interpretable AI

12 Feb 2020

Finally, we argue it is also important that AI systems warn their user when they are asked to perform outside their domain of applicability.

AUTONOMOUS VEHICLES

Modeling Sensing and Perception Errors towards Robust Decision Making in Autonomous Vehicles

31 Jan 2020

Sensing and Perception (S&P) is a crucial component of an autonomous system (such as a robot), especially when deployed in highly dynamic environments where it is required to react to unexpected situations.

AUTONOMOUS VEHICLES DECISION MAKING

Survey of Deep Reinforcement Learning for Motion Planning of Autonomous Vehicles

30 Jan 2020

Another part of research focuses on different layers of Motion Planning, such as strategic decisions, trajectory planning, and control.

AUTONOMOUS DRIVING DECISION MAKING MOTION PLANNING

Adversarial Attacks on Convolutional Neural Networks in Facial Recognition Domain

30 Jan 2020

Next, we craft a variety of different attack algorithms on a facial image dataset, with the intention of developing untargeted black-box approaches assuming minimal adversarial knowledge, to further assess the robustness of DNNs in the facial recognition realm.

AUTONOMOUS VEHICLES

Challenges and Countermeasures for Adversarial Attacks on Deep Reinforcement Learning

27 Jan 2020

Deep Reinforcement Learning (DRL) has numerous applications in the real world thanks to its outstanding ability in quickly adapting to the surrounding environments.

AUTONOMOUS VEHICLES