Visual Tracking

173 papers with code • 10 benchmarks • 27 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


Use these libraries to find Visual Tracking models and implementations
7 papers
3 papers
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Most implemented papers

SiamRPN++: Evolution of Siamese Visual Tracking with Very Deep Networks

STVIR/pysot 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.

Re3 : Real-Time Recurrent Regression Networks for Visual Tracking of Generic Objects

natdebru/OpenCV-Video-Label 17 May 2017

Robust object tracking requires knowledge and understanding of the object being tracked: its appearance, its motion, and how it changes over time.

SiamFC++: Towards Robust and Accurate Visual Tracking with Target Estimation Guidelines

MegviiDetection/video_analyst 14 Nov 2019

Following these guidelines, we design our Fully Convolutional Siamese tracker++ (SiamFC++) by introducing both classification and target state estimation branch(G1), classification score without ambiguity(G2), tracking without prior knowledge(G3), and estimation quality score(G4).

DCFNet: Discriminant Correlation Filters Network for Visual Tracking

foolwood/DCFNet 13 Apr 2017

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 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 CVPR 2019

Siamese networks have drawn great attention in visual tracking because of their balanced accuracy and speed.

ATOM: Accurate Tracking by Overlap Maximization

visionml/pytracking CVPR 2019

We argue that this approach is fundamentally limited since target estimation is a complex task, requiring high-level knowledge about the object.

SiamVGG: Visual Tracking using Deeper Siamese Networks

leeyeehoo/SiamVGG 7 Feb 2019

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.

Long-term Frame-Event Visual Tracking: Benchmark Dataset and Baseline

event-ahu/felt_sot_benchmark 9 Mar 2024

Current event-/frame-event based trackers undergo evaluation on short-term tracking datasets, however, the tracking of real-world scenarios involves long-term tracking, and the performance of existing tracking algorithms in these scenarios remains unclear.