no code implementations • 16 Jan 2021 • Namdar Homayounfar, Justin Liang, Wei-Chiu Ma, Raquel Urtasun
Towards this goal, in this paper we propose a bottom up approach where given a single click for each object in a video, we obtain the segmentation masks of these objects in the full video.
no code implementations • ICCV 2019 • Namdar Homayounfar, Wei-Chiu Ma, Justin Liang, Xinyu Wu, Jack Fan, Raquel Urtasun
One of the fundamental challenges to scale self-driving is being able to create accurate high definition maps (HD maps) with low cost.
no code implementations • CVPR 2018 • Namdar Homayounfar, Wei-Chiu Ma, Shrinidhi Kowshika Lakshmikanth, Raquel Urtasun
In this paper, we tackle the problem of online road network extraction from sparse 3D point clouds.
no code implementations • CVPR 2019 • Justin Liang, Namdar Homayounfar, Wei-Chiu Ma, Shenlong Wang, Raquel Urtasun
Creating high definition maps that contain precise information of static elements of the scene is of utmost importance for enabling self driving cars to drive safely.
no code implementations • 30 Jul 2020 • Namdar Homayounfar, Yuwen Xiong, Justin Liang, Wei-Chiu Ma, Raquel Urtasun
Obtaining precise instance segmentation masks is of high importance in many modern applications such as robotic manipulation and autonomous driving.
no code implementations • CVPR 2020 • Justin Liang, Namdar Homayounfar, Wei-Chiu Ma, Yuwen Xiong, Rui Hu, Raquel Urtasun
In this paper, we propose PolyTransform, a novel instance segmentation algorithm that produces precise, geometry-preserving masks by combining the strengths of prevailing segmentation approaches and modern polygon-based methods.
Ranked #1000000000 on Instance Segmentation on Cityscapes test (using extra training data)
no code implementations • 8 Aug 2019 • Wei-Chiu Ma, Ignacio Tartavull, Ioan Andrei Bârsan, Shenlong Wang, Min Bai, Gellert Mattyus, Namdar Homayounfar, Shrinidhi Kowshika Lakshmikanth, Andrei Pokrovsky, Raquel Urtasun
In this paper we propose a novel semantic localization algorithm that exploits multiple sensors and has precision on the order of a few centimeters.
no code implementations • 4 May 2019 • Min Bai, Gellert Mattyus, Namdar Homayounfar, Shenlong Wang, Shrinidhi Kowshika Lakshmikanth, Raquel Urtasun
Reliable and accurate lane detection has been a long-standing problem in the field of autonomous driving.
no code implementations • CVPR 2017 • Namdar Homayounfar, Sanja Fidler, Raquel Urtasun
In this work, we propose a novel way of efficiently localizing a sports field from a single broadcast image of the game.
no code implementations • 10 Apr 2016 • Namdar Homayounfar, Sanja Fidler, Raquel Urtasun
In this work, we propose a novel way of efficiently localizing a soccer field from a single broadcast image of the game.