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Online Visual Tracking with One-Shot Context-Aware Domain Adaptation
[article]
2021
arXiv
pre-print
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Online learning policy makes visual trackers more robust against different distortions through learning domain-specific cues. ...
However, the trackers adopting this policy fail to fully leverage the discriminative context of the background areas. ...
Visual object tracking is a fundamental task for human-machine interaction, autonomous driving, visual sports analysis, virtual reality, and human motion analysis. ...
arXiv:2008.09891v2
fatcat:2o57dm6rozggrin6pun6fwwtpq
Tracking by Joint Local and Global Search: A Target-aware Attention based Approach
[article]
2021
arXiv
pre-print
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In the tracking procedure, we integrate the target-aware attention with multiple trackers by exploring candidate search regions for robust tracking. ...
In this paper, we propose a novel and general target-aware attention mechanism (termed TANet) and integrate it with tracking-by-detection framework to conduct joint local and global search for robust tracking ...
Visualization In addition to the aforementioned quantitative analysis, we also give some visualization about the learned target-aware Target-Aware Attention. ...
arXiv:2106.04840v1
fatcat:3pktzebc6vfzrmr7ueu7l7qpd4
GraspARL: Dynamic Grasping via Adversarial Reinforcement Learning
[article]
2022
arXiv
pre-print
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In this work, we introduce an adversarial reinforcement learning framework for dynamic grasping, namely GraspARL. ...
Conventional approaches rely on a set of manually defined object motion patterns for training, resulting in poor generalization to unseen object trajectories. ...
We would also like to thanks the lab mates for the helpful discussion. ...
arXiv:2203.02119v2
fatcat:h7rbwcv2jrg7fozipm5ypk4s5u
MFGNet: Dynamic Modality-Aware Filter Generation for RGB-T Tracking
[article]
2022
arXiv
pre-print
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convolutional kernels for various input images in practical tracking. ...
The spatial and temporal recurrent neural network is used to capture the direction-aware context for accurate global attention prediction. ...
We adopt DFN for robust feature learning to mine the modality-aware context information for robust RGB-T tracking. Attention Mechanism. ...
arXiv:2107.10433v2
fatcat:3mxe5iidvrgbvbxdna4pwwlv74
You Only Demonstrate Once: Category-Level Manipulation from Single Visual Demonstration
[article]
2022
arXiv
pre-print
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For the latter part, a category-level behavior cloning (CatBC) method leverages motion tracking to perform closed-loop control. ...
Extensive experiments demonstrate its efficacy in a range of challenging industrial tasks in highprecision assembly, which involve learning complex, long-horizon policies. ...
Model-free 6 DoF Object Motion Tracking This work utilizes 6 DoF motion tracking for 2 purposes. ...
arXiv:2201.12716v2
fatcat:qbgchamnlvfvhhu6avtulp6yq4
Graph-Structured Visual Imitation
[article]
2020
arXiv
pre-print
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multiple visual entity detectors for each demonstration without human annotations or robot interactions. ...
Our robotic agent is rewarded when its actions result in better matching of relative spatial configurations for corresponding visual entities detected in its workspace and teacher's demonstration. ...
Conclusion We proposed encoding video frames in terms of visual entities and their spatial relationships, and we used this encoding to compute a perceptual cost function for visual imitation. ...
arXiv:1907.05518v2
fatcat:2rkz4bj3prgc5cgkhhjcrpfpmm
Table of Contents
2021
IEEE Robotics and Automation Letters
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Xie 5573 A Robust Optical Flow Tracking Method Based On Prediction Model for Visual-Inertial Odometry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...
Ren 4923 Learning Barrier Functions With Memory for Robust Safe Navigation . . . . K. Long, C. Qian, J. Cortés, and N. ...
doi:10.1109/lra.2021.3095987
fatcat:uyk6vlvv45hifbzj4ruzdi6w54
Deep Drone Racing: Learning Agile Flight in Dynamic Environments
[article]
2018
arXiv
pre-print
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We demonstrate our method in autonomous agile flight scenarios, in which a vision-based quadrotor traverses drone-racing tracks with possibly moving gates. ...
The CNN directly maps raw images into a robust representation in the form of a waypoint and desired speed. ...
The system combines the robust perceptual awareness of modern machine learning pipelines with the stability and speed of well-known control algorithms. ...
arXiv:1806.08548v3
fatcat:qolj5xr5svf6ta4wqvpz7xr55e
Deep Learning for Visual Tracking: A Comprehensive Survey
[article]
2019
arXiv
pre-print
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It also extensively evaluates and analyzes the leading visual tracking methods. ...
Visual target tracking is one of the most sought-after yet challenging research topics in computer vision. ...
Kamal Nasrollahi (Visual Analysis of People Lab (VAP), Aalborg University) for his beneficial comments. ...
arXiv:1912.00535v1
fatcat:v5ikqi2cpbblhgtkiu6z6l5anq
Deep Drone Racing: From Simulation to Reality With Domain Randomization
2019
IEEE Transactions on robotics
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2019 pre-print arXiv:1905.09727v1 fatcat:patqks7efver5jzs35xoxu7tgqOther Versions
A racing drone must traverse a track with possibly moving gates at high speed. ...
We enable this functionality by combining the performance of a state-of-the-art planning and control system with the perceptual awareness of a convolutional neural network (CNN). ...
As a result, the system combines the robust perceptual awareness of modern machine learning pipelines with the precision and speed of well-known control algorithms. ...
doi:10.1109/tro.2019.2942989
fatcat:u65own2qmvcmxkglwlmduyedfi
Learning to Jump from Pixels
[article]
2021
arXiv
pre-print
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The requirement for agility and terrain awareness in this setting reinforces the need for robust control. ...
Such dynamic motion results in significant motion of onboard sensors, which introduces a new set of challenges for real-time visual processing. ...
We are grateful to Elijah Stanger-Jones for his support in working with the robot hardware and electronics. ...
arXiv:2110.15344v1
fatcat:fr3wyu4udfhvjbqod6hog33l6u
Socially-Aware Multi-Agent Following with 2D Laser Scans via Deep Reinforcement Learning and Potential Field
[article]
2021
arXiv
pre-print
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In this paper, we propose a multi-agent method for an arbitrary number of robots to follow the target in a socially-aware manner using only 2D laser scans. ...
Specifically, with the help of laser scans in obstacle map representation, the learning-based policy can help the robots avoid collisions with both static obstacles and dynamic obstacles like pedestrians ...
Imitation learning based ones learn the tracking policy from expert demonstrations. ...
arXiv:2109.01874v1
fatcat:4nbqyrdqkzbtzid46bfy5aob5i
2019 Index IEEE Robotics and Automation Letters Vol. 4
2019
IEEE Robotics and Automation Letters
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Guo, Y., +, LRA July 2019 2801-2806 Deep Visual MPC-Policy Learning for Navigation. ...
., +, LRA Oct. 2019 4094-4101 Provably Robust Learning-Based Approach for High-Accuracy Tracking Control of Lagrangian Systems. ...
Permanent magnets Adaptive Dynamic Control for Magnetically Actuated Medical Robots. ...
doi:10.1109/lra.2019.2955867
fatcat:ckastwefh5chhamsravandtnx4
Catch Carry: Reusable Neural Controllers for Vision-Guided Whole-Body Tasks
[article]
2020
arXiv
pre-print
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We demonstrate the utility of our approach for several tasks, including goal-conditioned box carrying and ball catching, and we characterize its behavioral robustness. ...
We develop an integrated neural-network based approach consisting of a motor primitive module, human demonstrations, and an instructed reinforcement learning regime with curricula and task variations. ...
studio visit, and Audiomotion Studios for services related to motion capture collection and clean up. ...
arXiv:1911.06636v2
fatcat:zjtpjueewbafjgqi5grgr6dcra
Real-time Perception meets Reactive Motion Generation
[article]
2017
arXiv
pre-print
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We also report on the lessons learned for system building. ...
All architectures rely on the same components for real-time perception and reactive motion generation to allow a quantitative evaluation. ...
Therefore, we opted for model-based visual tracking and querying SDFs only for a small subset of points on the robot. ...
arXiv:1703.03512v3
fatcat:y3y25efvw5fsjeqw6j3xh7glve
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