Visual Tracking
145 papers with code • 5 benchmarks • 19 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
Libraries
Use these libraries to find Visual Tracking models and implementations
OTB
LaSOT
OTB-2015
TrackingNet
OTB-2013
OxUva
TNL2K
CDTB
VOT2014
Most implemented papers
Re3 : Real-Time Recurrent Regression Networks for Visual Tracking of Generic Objects
natdebru/OpenCV-Video-Label
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Robust object tracking requires knowledge and understanding of the object being tracked: its appearance, its motion, and how it changes over time.
SiamRPN++: Evolution of Siamese Visual Tracking with Very Deep Networks
STVIR/pysot
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CVPR 2019
Moreover, we propose a new model architecture to perform depth-wise and layer-wise aggregations, which not only further improves the accuracy but also reduces the model size.
DCFNet: Discriminant Correlation Filters Network for Visual Tracking
In this work, we present an end-to-end lightweight network architecture, namely DCFNet, to learn the convolutional features and perform the correlation tracking process simultaneously.
High Performance Visual Tracking With Siamese Region Proposal Network
foolwood/DaSiamRPN
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CVPR 2018
Visual object tracking has been a fundamental topic in recent years and many deep learning based trackers have achieved state-of-the-art performance on multiple benchmarks.
Deeper and Wider Siamese Networks for Real-Time Visual Tracking
researchmm/SiamDW
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CVPR 2019
Siamese networks have drawn great attention in visual tracking because of their balanced accuracy and speed.
SiamVGG: Visual Tracking using Deeper Siamese Networks
It combines a Convolutional Neural Network (CNN) backbone and a cross-correlation operator, and takes advantage of the features from exemplary images for more accurate object tracking.
Real-Time MDNet
IlchaeJung/RT-MDNet
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ECCV 2018
We present a fast and accurate visual tracking algorithm based on the multi-domain convolutional neural network (MDNet).
Learning regression and verification networks for long-term visual tracking
xiaobai1217/MBMD
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Compared with short-term tracking, the long-term tracking task requires determining the tracked object is present or absent, and then estimating the accurate bounding box if present or conducting image-wide re-detection if absent.
ATOM: Accurate Tracking by Overlap Maximization
visionml/pytracking
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CVPR 2019
We argue that this approach is fundamentally limited since target estimation is a complex task, requiring high-level knowledge about the object.
Fast Online Object Tracking and Segmentation: A Unifying Approach
foolwood/SiamMask
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CVPR 2019
In this paper we illustrate how to perform both visual object tracking and semi-supervised video object segmentation, in real-time, with a single simple approach.
