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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
    • Faster R-CNN Towards Real-Time Object Detection with Region Proposal Networks (tpami17) (pdf, notes)
    • RFCN - Object Detection via Region-based Fully Convolutional Networks (nips16) (pdf, notes) [Microsoft Research]
    • Mask R-CNN (iccv17) (pdf, (notes, arxiv, code (keras), code (tensorflow)) [Facebook AI Research]
  • 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)

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) (pdf, arxiv, code) [Microsoft Research]
    • 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 page, notes)
  • Reinforcement Learning
  • Network Flow
    • Near-Online Multi-target Tracking with Aggregated Local Flow Descriptor (iccv15) (NEC Labs) (pdf, author page, notes)
    • Deep Network Flow for Multi-Object Tracking (cvpr17) (NEC Labs) (pdf, supplementary, notes)
  • Graph Optimization
    • 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)
  • Baseline
    • Simple Online and Realtime Tracking (icip16) (pdf, notes, code)
    • High-Speed Tracking-by-Detection Without Using Image Information (avss17) (pdf, notes, code)

Single Object Tracking

  • Reinforcement Learning
    • 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 (cvpr17) (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)
  • Siamese
    • High Performance Visual Tracking with Siamese Region Proposal Network [cvpr18] [pdf] [author] [notes]

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 (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

Collections

Tutorials

Code