近三年_目标跟踪_45篇顶会论文整理

目标跟踪_顶会文章整理

大家好,这里是【来一块葱花饼】,这次带来了目标跟踪的论文分享,与你分享~

之前做了一段时间的目标跟踪算法(以单目标跟踪SOT为主)的研究,学习了四十多篇顶会论文。所以,我新成立了专栏目标跟踪(SOT)|顶会论文|学习笔记,论文笔记与大家分享,方便大家快速了解目标跟踪的进展,掌握不同算法思想。欢迎大家讨论,在评论区写出自己的想法~

本文是汇总的相关论文名称,方便大家查找,最后面有关于近三年的目标跟踪发展趋势。具体论文分析笔记,见专栏中的其他文章,欢迎关注。

具体论文分析笔记,见专栏中的其他文章,欢迎大家关注,链接如下:
目标跟踪|近三年|45篇顶会论文整理
目标跟踪|七大数据集|整理
目标跟踪|论文笔记分享|ICCV-6篇
目标跟踪|论文笔记分享|ICCV-2篇
目标跟踪|论文笔记分享|ECCV-6篇
目标跟踪|论文笔记分享|CVPR-12篇
目标跟踪|论文笔记分享|CVPR-10篇(1)
目标跟踪|论文笔记分享|CVPR-10篇(2)

文章目录

  • 目标跟踪_顶会文章整理
    • ICCV-2021-6篇
    • CVPR-2021-10篇
    • CVPR-2020-10篇
    • ECCV-2020-6篇
    • CVPR-2019-12篇
    • ICCV-2019-2篇
  • 整体发展趋势
    • 2019年
    • 2020年
    • 2021年

ICCV-2021-6篇

论文题目
Learning to Track Objects from Unlabeled Videos
Learning Spatio-Temporal Transformer for Visual Tracking
Learning to Adversarially Blur Visual Object Tracking
HiFT: Hierarchical Feature Transformer for Aerial Tracking
Learn to Match: Automatic Matching Network Design for Visual Tracking
Saliency-Associated Object Tracking

CVPR-2021-10篇

论文题目
Learning to Filter: Siamese Relation Network for Robust Tracking
STMTrack: Template-free Visual Tracking with Space-time Memory Networks
LightTrack: Finding Lightweight Neural Networks for Object Tracking via One-Shot Architecture Search
Alpha-Refine: Boosting Tracking Performance by Precise Bounding Box Estimation
Graph Attention Tracking
CapsuleRRT: Relationships-aware Regression Tracking via Capsules
Progressive Unsupervised Learning for Visual Object Tracking
Towards More Flexible and Accurate Object Tracking with Natural Language:Algorithms and Benchmark
Siamese Natural Language Tracker: Tracking by Natural Language Descriptions with Siamese Trackers
Rotation Equivariant Siamese Networks for Tracking

CVPR-2020-10篇

论文题目
SiamCAR: Siamese Fully Convolutional Classification and Regression for Visual Tracking
Siamese Box Adaptive Network for Visual Tracking
Deformable Siamese Attention Networks for Visual Object Tracking
Correlation-Guided Attention for Corner Detection Based Visual Tracking
Siam R-CNN: Visual Tracking by Re-Detection
Probabilistic Regression for Visual Tracking
Recursive Least-Squares Estimator-Aided Online Learning for Visual Tracking
ROAM: Recurrently Optimizing Tracking Model
One-Shot Adversarial Attacks on Visual Tracking With Dual Attention
AutoTrack: Towards High-Performance Visual Tracking for UAV With Automatic Spatio-Temporal Regularization

ECCV-2020-6篇

论文题目
PG-Net: Pixel to Global Matching Network for Visual Tracking
CLNet: A Compact Latent Network for Fast Adjusting Siamese Trackers
Learning Feature Embeddings for Discriminant Model based Tracking
Object Tracking using Spatio-Temporal Networks for Future Prediction Location
Know Your Surroundings: Exploiting Scene Information for Object Tracking
Tracking Emerges by Looking Around Static Scenes, with Neural 3D Mapping

CVPR-2019-12篇

论文题目
Unsupervised Deep Representation Learning for Real-Time Tracking
Tracking by Animation: Unsupervised Learning of Multi-Object Attentive Trackers
Object Tracking by Reconstruction With View-Specific Discriminative Correlation Filters
Target-Aware Deep Tracking
SPM-Tracker: Series-Parallel Matching for Real-Time Visual Object Tracking
SiamRPN++: Evolution of Siamese Visual Tracking With Very Deep Networks
Deeper and Wider Siamese Networks for Real-Time Visual Tracking
Graph Convolutional Tracking
ATOM: Accurate Tracking by Overlap Maximization
Visual Tracking via Adaptive Spatially-Regularized Correlation Filters
ROI Pooled Correlation Filters for Visual Tracking
Siamese Cascaded Region Proposal Networks for Real-Time Visual Tracking

ICCV-2019-2篇

论文题目
Learning Discriminative Model Prediction for Tracking
GradNet Gradient-Guided Network for Visual Object Tracking

整体发展趋势

2019年

CVPR-2019-12篇
ICCV-2019-2篇
19年的文章很多还是在讨论滤波器和使用基础方法改进siamese

2020年

CVPR-2020-10篇
ECCV-2020-6篇
20年很多使用了动态模板、anchor-free、提高精度等方法

2021年

CVPR-2021-10篇
ICCV-2021-6篇
21年则使用transformer、将cv和nlp结合,更关注形变、消失等跟踪问题,以及一些新的学习方法

之后我将在专栏目标跟踪(SOT)|顶会论文|学习笔记中,分享近三年的四十多篇顶会文章的详细笔记,方便大家快速入门。

感兴趣的同学点赞+收藏+关注,直接进入专栏进行学习~你们的支持就是我最大的动力~
感兴趣的同学点赞+收藏+关注,直接进入专栏进行学习~你们的支持就是我最大的动力~
感兴趣的同学点赞+收藏+关注,直接进入专栏进行学习~你们的支持就是我最大的动力~

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