Jie Li

According to our database, Jie Li authored at least 22 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Depth Is All You Need for Monocular 3D Detection.

Dennis Park, Jie Li, Dian Chen, Vitor Guizilini, Adrien Gaidon

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Simple-BEV: What Really Matters for Multi-Sensor BEV Perception?

Adam W. Harley, Zhaoyuan Fang, Jie Li, Rares Ambrus, Katerina Fragkiadaki

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Breaking the "Object" in Video Object Segmentation.

Pavel Tokmakov, Jie Li, Adrien Gaidon

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Standing Between Past and Future: Spatio-Temporal Modeling for Multi-Camera 3D Multi-Object Tracking.

Ziqi Pang, Jie Li, Pavel Tokmakov, Dian Chen, Sergey Zagoruyko, Yu-Xiong Wang

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Viewpoint Equivariance for Multi-View 3D Object Detection.

Dian Chen, Jie Li, Vitor Guizilini, Rares Ambrus, Adrien Gaidon

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

ShaSTA: Modeling Shape and 0031Spatio-Temporal Affinities for 3D Multi-Object Tracking.

Tara Sadjadpour, Jie Li, Rares Ambrus, Jeannette Bohg

CoRR, 2022

A Simple Baseline for BEV Perception Without LiDAR.

Adam W. Harley, Zhaoyuan Fang, Jie Li, Rares Ambrus, Katerina Fragkiadaki

CoRR, 2022

Object Permanence Emerges in a Random Walk along Memory.

Pavel Tokmakov, Allan Jabri, Jie Li, Adrien Gaidon

Proceedings of the International Conference on Machine Learning, 2022

SpOT: Spatiotemporal Modeling for 3D Object Tracking.

Colton Stearns, Davis Rempe, Jie Li, Rares Ambrus, Sergey Zakharov, Vitor Guizilini, Yanchao Yang, Leonidas J. Guibas

Proceedings of the Computer Vision - ECCV 2022, 2022

2021

Probabilistic 3D Multi-Modal, Multi-Object Tracking for Autonomous Driving.

Hsu-Kuang Chiu, Jie Li, Rares Ambrus, Jeannette Bohg

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Learning to Track with Object Permanence.

Pavel Tokmakov, Jie Li, Wolfram Burgard, Adrien Gaidon

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Is Pseudo-Lidar needed for Monocular 3D Object detection?

Dennis Park, Rares Ambrus, Vitor Guizilini, Jie Li, Adrien Gaidon

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Geometric Unsupervised Domain Adaptation for Semantic Segmentation.

Vitor Guizilini, Jie Li, Rares Ambrus, Adrien Gaidon

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Hierarchical Lovasz Embeddings for Proposal-Free Panoptic Segmentation.

Tommi Kerola, Jie Li, Atsushi Kanehira, Yasunori Kudo, Alexis Vallet, Adrien Gaidon

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

Probabilistic 3D Multi-Object Tracking for Autonomous Driving.

Hsu-Kuang Chiu, Antonio Prioletti, Jie Li, Jeannette Bohg

CoRR, 2020

PillarFlow: End-to-end Birds-eye-view Flow Estimation for Autonomous Driving.

Kuan-Hui Lee, Matthew Kliemann, Adrien Gaidon, Jie Li, Chao Fang, Sudeep Pillai, Wolfram Burgard

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

Semantically-Guided Representation Learning for Self-Supervised Monocular Depth.

Vitor Guizilini, Rui Hou, Jie Li, Rares Ambrus, Adrien Gaidon

Proceedings of the 8th International Conference on Learning Representations, 2020

Real-Time Panoptic Segmentation From Dense Detections.

Rui Hou, Jie Li, Arjun Bhargava, Allan Raventos, Vitor Guizilini, Chao Fang, Jerome P. Lynch, Adrien Gaidon

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

SPIGAN: Privileged Adversarial Learning from Simulation.

Kuan-Hui Lee, Germán Ros, Jie Li, Adrien Gaidon

Proceedings of the 7th International Conference on Learning Representations, 2019

Robust Semi-Supervised Monocular Depth Estimation with Reprojected Distances.

Vitor Guizilini, Jie Li, Rares Ambrus, Sudeep Pillai, Adrien Gaidon

Proceedings of the 3rd Annual Conference on Robot Learning, 2019

Two Stream Networks for Self-Supervised Ego-Motion Estimation.

Rares Ambrus, Vitor Guizilini, Jie Li, Sudeep Pillai, Adrien Gaidon

Proceedings of the 3rd Annual Conference on Robot Learning, 2019

2018

Learning to Fuse Things and Stuff.

Jie Li, Allan Raventos, Arjun Bhargava, Takaaki Tagawa, Adrien Gaidon

CoRR, 2018