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object tracking

Awesome Object Tracking based on abhineet123 github: https://github.com/abhineet123/Deep-Learning-for-Tracking-and-Detection

Survey

Deep Learning for Visual Tracking: A Comprehensive Survey

Deep Learning in Video Multi-Object Tracking: A Survey

  • intro: Multi-Object Tracking
  • arXiv: hhttps://arxiv.org/abs/1907.12740

A Review of Visual Trackers and Analysis of its Application to Mobile Robot

Collection of papers, datasets, code and other resources for object detection and tracking using deep learning

Papers

Static Detection

Region Proposal

  • Scalable Object Detection Using Deep Neural Networks [cvpr14] [pdf] [notes]
  • Selective Search for Object Recognition [ijcv2013] [pdf] [notes]

RCNN

YOLO

  • You Only Look Once Unified, Real-Time Object Detection [ax1605] [pdf] [notes]
  • YOLO9000 Better, Faster, Stronger [ax1612] [pdf] [notes]
  • YOLOv3 An Incremental Improvement [ax1804] [pdf] [notes]

SSD

  • SSD Single Shot MultiBox Detector [ax1612/eccv16] [pdf] [notes]
  • DSSD Deconvolutional Single Shot Detector [ax1701] [pdf] [notes]

RetinaNet

  • Feature Pyramid Networks for Object Detection [ax1704] [pdf] [notes]
  • Focal Loss for Dense Object Detection [ax180207/iccv17] [pdf] [notes]

Misc

  • OverFeat Integrated Recognition, Localization and Detection using Convolutional Networks [ax1402/iclr14] [pdf] [notes]
  • LSDA Large scale detection through adaptation [ax1411/nips14] [pdf] [notes]
  • Acquisition of Localization Confidence for Accurate Object Detection [ax1807/eccv18] [pdf] [notes] [code]

Video Detection

Tubelet

  • Object Detection from Video Tubelets with Convolutional Neural Networks [cvpr16] [pdf] [notes]
  • Object Detection in Videos with Tubelet Proposal Networks [ax1704/cvpr17] [pdf] [notes]

FGFA

  • Deep Feature Flow for Video Recognition [cvpr17] [Microsoft Research] [pdf] [arxiv] [code]
  • Flow-Guided Feature Aggregation for Video Object Detection [ax1708/iccv17] [pdf] [notes]
  • Towards High Performance Video Object Detection [ax1711] [Microsoft] [pdf] [notes]

RNN

  • Online Video Object Detection using Association LSTM [iccv17] [pdf] [notes]
  • Context Matters Refining Object Detection in Video with Recurrent Neural Networks [bmvc16] [pdf] [notes]

Multi Object Tracking

Deep Learning

  • Tracking The Untrackable: Learning To Track Multiple Cues with Long-Term Dependencies [ax1704/iccv17] [Stanford] [pdf] [arxiv] [project], [notes]
  • Online Multi-Object Tracking Using CNN-based Single Object Tracker with Spatial-Temporal Attention Mechanism [ax1708/iccv17] [pdf] [arxiv] [notes]
  • Online multi-object tracking with dual matching attention networks [ax1902/eccv18] [pdf] [arxiv] [notes] [code]

Unsupervised Learning

  • Tracking by Animation: Unsupervised Learning of Multi-Object Attentive Trackers [ax1809/cvpr19] [pdf] [arxiv] [notes] [code]

Reinforcement Learning

Network Flow

Graph Optimization

  • A Multi-cut Formulation for Joint Segmentation and Tracking of Multiple Objects [ax1607] [highest MT on MOT2015] [University of Freiburg, Germany] [pdf] [arxiv] [author] [notes]

Baseline

Single Object Tracking

Reinforcement Learning

  • Deep Reinforcement Learning for Visual Object Tracking in Videos [ax1704] [USC-Santa Barbara, Samsung Research] [pdf] [arxiv] [author] [notes]
  • Visual Tracking by Reinforced Decision Making [ax1702] [Seoul National University, Chung-Ang University] [pdf] [arxiv] [author]
    [notes]
  • Action-Decision Networks for Visual Tracking with Deep Reinforcement Learning [cvpr17] [Seoul National University] [pdf] [supplementary] [project] [notes] [code]
  • End-to-end Active Object Tracking via Reinforcement Learning [ax1705] [Peking University, Tencent AI Lab] [pdf] [arxiv]

Siamese

Misc

Deep Learning

  • Do Deep Nets Really Need to be Deep [nips14] [pdf] [notes]

Synthetic Gradients

  • Decoupled Neural Interfaces using Synthetic Gradients [ax1608] [pdf] [notes]
  • Understanding Synthetic Gradients and Decoupled Neural Interfaces [ax1703] [pdf] [notes]

Unsupervised Learning

  • Learning Features by Watching Objects Move (cvpr17) [pdf] [notes]

Interpolation

Autoencoder

Variational

  • beta-VAE Learning Basic Visual Concepts with a Constrained Variational Framework [iclr17] [pdf] [notes]
  • Disentangling by Factorising [ax1806] [pdf] [notes]

Datasets

Multi Object Tracking

Single Object Tracking

Video Detection

Video Understanding / Activity Recognition

Static Detection

Animals

Boundary Detection

Static Segmentation

Video Segmentation

Classification

Optical Flow

Code

Multi Object Tracking

Single Object Tracking

GUI Application / Large Scale Tracking / Animals

Video Detection

Static Detection and Matching

Frameworks

Region Proposal

FPN

RCNN

SSD

YOLO

Misc

Matching

Boundary Detection

Optical Flow

Instance Segmentation

Frameworks

Semantic Segmentation

Video Segmentation

Autoencoders

Classification

Misc

Collections

Datasets

Single Object Tracking

Multi Object Tracking

Segmentation

Deep Compressed Sensing

Misc

Tutorials

Static Detection

Video Detection

Instance Segmentation

Deep RL

Autoencoders