/Deep-Learning-for-Tracking-and-Detection

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

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

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 ax16_12 (pdf, notes)
    • YOLOv3 An Incremental Improvement ax180408 (pdf, notes)
  • SSD
    • SSD Single Shot MultiBox Detector eccv16_ax16_12 (pdf, notes)
    • DSSD Deconvolutional Single Shot Detector ax1701.06659 (pdf, notes)
  • RetinaNet
    • Feature Pyramid Networks for Object Detection ax170419 (pdf, notes)
    • Focal Loss for Dense Object Detection ax180207 (pdf, notes)
  • Misc
    • OverFeat Integrated Recognition, Localization and Detection using Convolutional Networks ax1402 iclr14 (pdf, notes)
    • LSDA Large scale detection through adaptation nips14 ax14_11 (pdf, notes)

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 (pdf, arxiv, code) [Microsoft Research]
    • Flow-Guided Feature Aggregation for Video Object Detection ax1708 iccv17 (pdf, notes)
    • Towards High Performance Video Object Detection ax171130 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

  • Learning to Track: Online Multi-object Tracking by Decision Making (ICCV 2015) (Stanford) (pdf, code (Matlab), project page, notes)
  • Tracking The Untrackable: Learning To Track Multiple Cues with Long-Term Dependencies (arxiv April 2017) (Stanford) (pdf, arxiv, project page, notes)
  • Near-Online Multi-target Tracking with Aggregated Local Flow Descriptor (ICCV 2015) (NEC Labs) (pdf, author page, notes)
  • A Multi-cut Formulation for Joint Segmentation and Tracking of Multiple Objects (arxiv July 2016) (highest MT on MOT2015) (University of Freiburg, Germany) (pdf, arxiv, author page, notes)
  • Deep Network Flow for Multi-Object Tracking (CVPR 2017) (NEC Labs) (pdf, supplementary, notes)

Single Object Tracking

  • Deep Reinforcement Learning for Visual Object Tracking in Videos (arxiv April 2017) (USC-Santa Barbara, Samsung Research) (pdf, arxiv, author page, notes)
  • Visual Tracking by Reinforced Decision Making (arxiv February 2017) (Seoul National University, Chung-Ang University) (pdf, arxiv, author page, notes)
  • Action-Decision Networks for Visual Tracking with Deep Reinforcement Learning (CVPR 2017) (Seoul National University) (pdf, supplementary, project page, notes)
  • End-to-end Active Object Tracking via Reinforcement Learning (arxiv 30 May 2017) (Peking University, Tencent AI Lab) (pdf, arxiv)

Deep Learning

  • Do Deep Nets Really Need to be Deep (NIPS 2014) (pdf, notes)
  • Synthetic Gradients
    • Decoupled Neural Interfaces using Synthetic Gradients (arxiv August 2016) (pdf, notes)
    • Understanding Synthetic Gradients and Decoupled Neural Interfaces (arxiv March 2017) (pdf, notes)

Unsupervised Learning

  • Learning Features by Watching Objects Move (CVPR 2017) (pdf, notes)

Interpolation

Datasets

Collections

Tutorials

Code

Presentations (Access Restricted to my research group)