A self-driving car is a vehicle capable of sensing its environment and navigating autonomously without human intervention. Autonomous cars can interpret its environment using sensors such as radar, lidar, GPS, odometry, and computer vision, being computer vision one of the most challenging and promising techniques thanks to the Deep Learning technology.
Computer Vision allows to detect and track obstacles (e.g., pedestrians, vehicles, cyclists, traffic signs) perform scene understanding, 3D reconstruction or free space computation among others. Advanced simulation is crucial to train and test the system in corner cases where it is difficult to acquire enough annotated data.
The goal of the project is to design and develop a perception-based self-driving system for urban scenarios, performing a real life test at the UAB campus. The fellow will have the opportunity to work and lead Ph.D. and Master Students in different deep learning topics applied to autonomous driving such:
- Object detection
- End-to-End driving
- Visual localization and odometry
- 3D reconstruction
- Scene understanding
- Free space computation
- Lane detection
PROJECT SUPERVISOR & HOSTING GROUP
Prof. Antonio M. López will supervise the Fellow. Prof. Antonio Lopez is the leader of the Advanced Driver Assistance Systems team at the CVC (ADAS). The team has 10 years of experience in ADAS and autonomous vehicles developing such systems for companies like Volkswagen, SEAT, IDIADA, or Samsung.
Currently, ADAS is developing an autonomous car (http://adas.cvc.uab.es/site/elektra). It is an electric vehicle fully automatized and equipped with cameras, GPS, IMU and computing power. The vehicle has already control & planning algorithms, high definition maps for precise localization, environment perception (e.g., Obstacle detection and tracking, scene understanding, 3D reconstruction, free space computation) and V2X communications.
NVIDIA is one of the key partners of the project providing us hardware and prototypes such as Drive PX. With DRIVE PX we are able of boosting the development of our project faster than other groups.
Our research focus on vision-based scene understanding for autonomous driving, specially supported by reinforcement and deep learning. For aspects beyond scene understanding, such as real-time computing, vehicle-to-X communications, control and planning, etc., we have the support of other research groups too
This is a very ambitious project and one of the strategic lines of the CVC. It is totally alienated with the H2020, RIS3Cat and Spanish challenges as well as with the industry interests. In this context, ADAS is currently developing 2 main projects: ACDC (Automated and Connected Driving in the City) and SYNTHIA (www.synthia-dataset.net).
The Hosting group has several international collaborations with mutual exchanges of Ph.D. students and post-docs. Examples of such close collaborations are: MILA – Université de Montreal (Montreal, Canada), Daimler AG (Stuttgart, Germany), Toshiba Research Europe (Cambridge, UK), Toshiba Research and Development Center (Kawasaki, Japan), NICTA (Canberra, Australia).
The candidate should possess a PhD in computer vision or machine learning, and have a strong publication record. We especially encourage candidates with experience in Deep Learning to apply, but other backgrounds in computer vision and machine learning will also be considered.
The applicants are expected to be fluent in both oral and written communication in English. They should work well in a team, while demonstrating initiative and independence, and willing to supervise Ph.D. students.
THE COMPUTER VISION CENTER
The selected candidate will work in the Computer Vision Centre (CVC), Barcelona, a research institute comprising more than 100 researchers and support staff, dedicated to computer vision research and knowledge transfer. With a strong international projection and links to the industry, the Computer Vision Centre offers an exciting environment for scientific career development.
The Computer Vision Centre has a plan for expansion of its permanent research staff base, and has received the “HR Excellence in Research” award as a provider and supporter of a stimulating and favourable working environment.
Antonio M. López
+34 93 581 25 61
Conditions, deadlines and applications at www.uab.cat/psphere.
Call open from 9th of September until 9th of December.
OTHER P-SPHERE POSITIONS OPEN AT CVC
- HUMAN POSE RECOVERY AND BEHAVIOR ANALYSIS
- SCENE TEXT UNDERSTANDING
- PREDICTING INTRINSIC PROPERTIES FROM IMAGES USING DEEP NETWORKS
- INFORMATION EXTRACTION FROM HISTORICAL DOCUMENT IMAGES
- DEEP LEARNING FOR MULTI-MODAL DATA REPRESENTATIONS