Search Results for author: Justin Liang

Found 8 papers, 0 papers with code

Mending Neural Implicit Modeling for 3D Vehicle Reconstruction in the Wild

no code implementations18 Jan 2021 Shivam Duggal, ZiHao Wang, Wei-Chiu Ma, Sivabalan Manivasagam, Justin Liang, Shenlong Wang, Raquel Urtasun

Reconstructing high-quality 3D objects from sparse, partial observations from a single view is of crucial importance for various applications in computer vision, robotics, and graphics.

3D Object Reconstruction

VideoClick: Video Object Segmentation with a Single Click

no code implementations16 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.

Segmentation Semantic Segmentation +3

DAGMapper: Learning to Map by Discovering Lane Topology

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.

End-to-End Deep Structured Models for Drawing Crosswalks

no code implementations ECCV 2018 Justin Liang, Raquel Urtasun

In this paper we address the problem of detecting crosswalks from LiDAR and camera imagery.

Convolutional Recurrent Network for Road Boundary Extraction

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.

Self-Driving Cars

LevelSet R-CNN: A Deep Variational Method for Instance Segmentation

no code implementations30 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.

Autonomous Driving Instance Segmentation +2

PolyTransform: Deep Polygon Transformer for Instance Segmentation

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 #1 on Instance Segmentation on Cityscapes test (using extra training data)

Instance Segmentation Segmentation +2

TorontoCity: Seeing the World with a Million Eyes

no code implementations ICCV 2017 Shenlong Wang, Min Bai, Gellert Mattyus, Hang Chu, Wenjie Luo, Bin Yang, Justin Liang, Joel Cheverie, Sanja Fidler, Raquel Urtasun

In this paper we introduce the TorontoCity benchmark, which covers the full greater Toronto area (GTA) with 712. 5 $km^2$ of land, 8439 $km$ of road and around 400, 000 buildings.

Instance Segmentation Semantic Segmentation

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