Visual Object Tracking

86 papers with code • 16 benchmarks • 16 datasets

Visual Object Tracking is an important research topic in computer vision, image understanding and pattern recognition. Given the initial state (centre location and scale) of a target in the first frame of a video sequence, the aim of Visual Object Tracking is to automatically obtain the states of the object in the subsequent video frames.

Source: Learning Adaptive Discriminative Correlation Filters via Temporal Consistency Preserving Spatial Feature Selection for Robust Visual Object Tracking

Greatest papers with code

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.

Translation Visual Object Tracking +1

Fast Online Object Tracking and Segmentation: A Unifying Approach

foolwood/SiamMask 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.

Real-Time Visual Tracking Semi-Supervised Semantic Segmentation +2

Learning Target Candidate Association to Keep Track of What Not to Track

visionml/pytracking ICCV 2021

To tackle the problem of lacking ground-truth correspondences between distractor objects in visual tracking, we propose a training strategy that combines partial annotations with self-supervision.

Visual Object Tracking Visual Tracking

Learning Discriminative Model Prediction for Tracking

visionml/pytracking ICCV 2019

The current strive towards end-to-end trainable computer vision systems imposes major challenges for the task of visual tracking.

Visual Object Tracking Visual Tracking

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.

General Classification Visual Object Tracking +1

Rethinking Self-supervised Correspondence Learning: A Video Frame-level Similarity Perspective

open-mmlab/mmaction2 ICCV 2021

To learn generalizable representation for correspondence in large-scale, a variety of self-supervised pretext tasks are proposed to explicitly perform object-level or patch-level similarity learning.

Contrastive Learning Semantic Segmentation +3

Distractor-aware Siamese Networks for Visual Object Tracking

foolwood/DaSiamRPN ECCV 2018

During the off-line training phase, an effective sampling strategy is introduced to control this distribution and make the model focus on the semantic distractors.

Incremental Learning Visual Object Tracking +1

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.

Fine-tuning Region Proposal +2

Spatially Supervised Recurrent Convolutional Neural Networks for Visual Object Tracking

Guanghan/ROLO 19 Jul 2016

In this paper, we develop a new approach of spatially supervised recurrent convolutional neural networks for visual object tracking.

Object Detection Visual Object Tracking

Ocean: Object-aware Anchor-free Tracking

researchmm/SiamDW ECCV 2020

In this paper, we propose a novel object-aware anchor-free network to address this issue.

Visual Object Tracking