activity
20192023
most citedMultiple Object Tracking by Flowing and Fusing

29 citations · 59 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CV2023

XVO: Generalized Visual Odometry via Cross-Modal Self-Training

Lei Lai, Zhongkai Shangguan, Jimuyang Zhang +1

We propose XVO, a semi-supervised learning method for training generalized monocular Visual Odometry (VO) models with robust off-the-self operation across diverse datasets and sett…

cs.CV2023

Coaching a Teachable Student

Jimuyang Zhang, Zanming Huang, Eshed Ohn-Bar

We propose a novel knowledge distillation framework for effectively teaching a sensorimotor student agent to drive from the supervision of a privileged teacher agent. Current disti…

cs.CV20221 cited

SelfD: Self-Learning Large-Scale Driving Policies From the Web

Jimuyang Zhang, Ruizhao Zhu, Eshed Ohn-Bar

Effectively utilizing the vast amounts of ego-centric navigation data that is freely available on the internet can advance generalized intelligent systems, i.e., to robustly scale…

cs.CV2021

Learning by Watching

Jimuyang Zhang, Eshed Ohn-Bar

When in a new situation or geographical location, human drivers have an extraordinary ability to watch others and learn maneuvers that they themselves may have never performed. In…

cs.CV202029 cited

Multiple Object Tracking by Flowing and Fusing

Jimuyang Zhang, Sanping Zhou, Xin Chang +4

Most of Multiple Object Tracking (MOT) approaches compute individual target features for two subtasks: estimating target-wise motions and conducting pair-wise Re-Identification (Re…

cs.CV201911 cited

Frame-wise Motion and Appearance for Real-time Multiple Object Tracking

Jimuyang Zhang, Sanping Zhou, Jinjun Wang +1

The main challenge of Multiple Object Tracking (MOT) is the efficiency in associating indefinite number of objects between video frames. Standard motion estimators used in tracking…