Seminar on Computer Science and Applied Mathematics
Matematički Institut SANU, Beograd
Knez Mihajlova 36
Fakultet organizacionih nauka, Univerzitet u Beogradu,
Jove Ilica 154
IEEE Chapter Computer Science (CO-16) Belgrade, Republic of Serbia
SEMINAR ZA RAČUNARSTVO I PRIMENJENU MATEMATIKU
MI SANU, Knez Mihailova 36, sala 301f
PLAN RADA SEMINARA ZA JUL 2021. GODINE
Zbog trenutne epidemiološke situacije, predavanja na seminaru će se održavati na daljinu, a slušaoci mogu da ih prate preko linka https://miteam.mi.sanu.ac.rs/asset/YoqHWKALRkRTbK9So.
UTORAK, 27.07.2021. u 14:15, sala 301f, MISANU i Online
Nemanja Đurić, Aurora Innovation, Inc., Pittsburgh, PA, USA
OBJECT DETECTION AND MOTION PREDICTION FOR SAFE SELF-DRIVING USING RASTER-BASED METHODS
Registracija za on-line praćenje predavanja na Seminaru je na linku https://miteam.mi.sanu.ac.rs/asset/xzGqvSp7aWbg8WpYX.
Object detection and motion prediction are critical components of self-driving technology, tasked with understanding the current state of the world and estimating how it will evolve in the near future. In the talk we focus on these important problems, and discuss raster-based methods developed at Uber ATG that have shown state-of-the-art performance. Such approaches encode the raw sensor data as top-down and/or front-view images of a surrounding area, providing near-complete contextual information necessary for accurate detection of traffic actors and their behavioral prediction. We present a number of recently proposed methods, ranging from models focusing solely on motion prediction to joint models that perform detection and prediction in an end-to-end fashion. We also discuss how to develop methods that obey map and other physical constraints of the traffic surroundings, resulting in more realistic predictions and improved modeling of uncertain environments in which the self-driving vehicles operate.
Zajednički sastanak AI seminara i Seminara za za računarstvo i primenjenu matematiku