Visual Tracking
170 papers with code • 9 benchmarks • 26 datasets
Visual Tracking is an essential and actively researched problem in the field of computer vision with various real-world applications such as robotic services, smart surveillance systems, autonomous driving, and human-computer interaction. It refers to the automatic estimation of the trajectory of an arbitrary target object, usually specified by a bounding box in the first frame, as it moves around in subsequent video frames.
Source: Learning Reinforced Attentional Representation for End-to-End Visual Tracking
Benchmarks
These leaderboards are used to track progress in Visual Tracking
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Libraries
Use these libraries to find Visual Tracking models and implementations
Kinetics
DAVIS
OTB
LaSOT
TrackingNet
OTB-2015
OTB-2013
TNL2K
Kubric
OxUva
Latest papers
Improving Underwater Visual Tracking With a Large Scale Dataset and Image Enhancement
The method has resulted in a significant performance improvement, of up to 5. 0% AUC, of state-of-the-art (SOTA) visual trackers.
Learning Visual Tracking and Reaching with Deep Reinforcement Learning on a UR10e Robotic Arm
The report describes the reinforcement learning environments created to facilitate policy learning with the UR10e, a robotic arm from Universal Robots, and presents our initial results in training deep Q-learning and proximal policy optimization agents on the developed reinforcement learning environments.
Integrating Boxes and Masks: A Multi-Object Framework for Unified Visual Tracking and Segmentation
Tracking any given object(s) spatially and temporally is a common purpose in Visual Object Tracking (VOT) and Video Object Segmentation (VOS).
CiteTracker: Correlating Image and Text for Visual Tracking
norahgreen/citetracker
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ICCV 2023
Existing visual tracking methods typically take an image patch as the reference of the target to perform tracking.
Towards Real-World Visual Tracking with Temporal Contexts
To handle those problems, we propose a two-level framework (TCTrack) that can exploit temporal contexts efficiently.
Robust Object Modeling for Visual Tracking
To enjoy the merits of both methods, we propose a robust object modeling framework for visual tracking (ROMTrack), which simultaneously models the inherent template and the hybrid template features.
TAPIR: Tracking Any Point with per-frame Initialization and temporal Refinement
We present a novel model for Tracking Any Point (TAP) that effectively tracks any queried point on any physical surface throughout a video sequence.
Cross-Drone Transformer Network for Robust Single Object Tracking
cgjacklin/transmdot
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IEEE Transactions on Circuits and Systems for Video Technology 2023
During the tracking process, a cross-drone mapping mechanism is proposed by using the surrounding information of the drone with promising tracking status as reference, assisting drones that lost targets to re-calibrate, which implements real-time cross-drone information interaction.
Estimation of control area in badminton doubles with pose information from top and back view drone videos
ning-d/drone_bd_controlarea
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In this work, we present the first annotated drone dataset from top and back views in badminton doubles and propose a framework to estimate the control area probability map, which can be used to evaluate teamwork performance.
Tracking through Containers and Occluders in the Wild
Tracking objects with persistence in cluttered and dynamic environments remains a difficult challenge for computer vision systems.
