← Back to papers
2019 AAAI AAAI 2019

Demo: Learning to Perceive Long-Range Obstacles Using Self-Supervision from Short-Range Sensors

Abstract

Abstract We demonstrate a self-supervised approach which learns to detect long-range obstacles from video: it automatically obtains training labels by associating the camera frames acquired at a given pose to short-range sensor readings acquired at a different pose.

🚀 Conference Pioneer — AAAI 2019
🌉 Interdisciplinary Bridge — Artificial Intelligence and Computer Vision and Deep Learning and Machine Learning
📈 Trend Setter — Self-Supervised Learning
🐣 Hot Topic Early Bird — sensor fusion
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio

Authors

Mirko Nava , Jérôme Guzzi , R. Omar Chavez-Garcia , Luca M. Gambardella , Alessandro Giusti

Topics

Artificial Intelligence > Core AI > Autonomous Vehicles Machine Learning > Learning Types > Self-Supervised Learning Computer Vision > Analysis > Object Detection Deep Learning > Learning Types > Self-Supervised Learning Artificial Intelligence > Learning Paradigms > Self-Supervised Learning

Keywords

computer vision self-supervised learning sensor fusion video analysis autonomous vehicle obstacle detection
Download PDF

Related papers

Cooperative Multimodal Approach to Depression Detection in Twitter 2019
Learning to Align Question and Answer Utterances in Customer Service Conversation with Recurrent Pointer Networks 2019
Community Detection in Social Networks Considering Topic Correlations 2019
Session-Based Recommendation with Graph Neural Networks 2019
Blameworthiness in Multi-Agent Settings 2019