Search Results for author: Fangwei Zhong

Found 7 papers, 2 papers with code

Towards Distraction-Robust Active Visual Tracking

no code implementations18 Jun 2021 Fangwei Zhong, Peng Sun, Wenhan Luo, Tingyun Yan, Yizhou Wang

In active visual tracking, it is notoriously difficult when distracting objects appear, as distractors often mislead the tracker by occluding the target or bringing a confusing appearance.

Visual Tracking

Learning Multi-Agent Coordination for Enhancing Target Coverage in Directional Sensor Networks

1 code implementation NeurIPS 2020 Jing Xu, Fangwei Zhong, Yizhou Wang

Maximum target coverage by adjusting the orientation of distributed sensors is an important problem in directional sensor networks (DSNs).

Pose-Assisted Multi-Camera Collaboration for Active Object Tracking

no code implementations15 Jan 2020 Jing Li, Jing Xu, Fangwei Zhong, Xiangyu Kong, Yu Qiao, Yizhou Wang

In the system, each camera is equipped with two controllers and a switcher: The vision-based controller tracks targets based on observed images.

Object Tracking

AD-VAT: An Asymmetric Dueling mechanism for learning Visual Active Tracking

no code implementations ICLR 2019 Fangwei Zhong, Peng Sun, Wenhan Luo, Tingyun Yan, Yizhou Wang

In AD-VAT, both the tracker and the target are approximated by end-to-end neural networks, and are trained via RL in a dueling/competitive manner: i. e., the tracker intends to lockup the target, while the target tries to escape from the tracker.

CRAVES: Controlling Robotic Arm with a Vision-based Economic System

1 code implementation CVPR 2019 Yiming Zuo, Weichao Qiu, Lingxi Xie, Fangwei Zhong, Yizhou Wang, Alan L. Yuille

We also construct a vision-based control system for task accomplishment, for which we train a reinforcement learning agent in a virtual environment and apply it to the real-world.

3D Pose Estimation Domain Adaptation

End-to-end Active Object Tracking and Its Real-world Deployment via Reinforcement Learning

no code implementations10 Aug 2018 Wenhan Luo, Peng Sun, Fangwei Zhong, Wei Liu, Tong Zhang, Yizhou Wang

We further propose an environment augmentation technique and a customized reward function, which are crucial for successful training.

Object Tracking

End-to-end Active Object Tracking via Reinforcement Learning

no code implementations ICML 2018 Wenhan Luo, Peng Sun, Fangwei Zhong, Wei Liu, Tong Zhang, Yizhou Wang

We study active object tracking, where a tracker takes as input the visual observation (i. e., frame sequence) and produces the camera control signal (e. g., move forward, turn left, etc.).

Object Tracking

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