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abhineet123 committed Dec 28, 2018
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!single_object_tracking/
!deep_rl/
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32 changes: 29 additions & 3 deletions ReadMe.md
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Expand Up @@ -15,6 +15,7 @@ Collection of papers and other resources for object detection and tracking using
[notes](static_detection/notes/Faster_R-CNN.pdf))
- **Mask R-CNN**
([pdf](static_detection/rcnn/Mask%20R-CNN%20ax17_4%20iccv17.pdf),
([notes](static_detection/notes/Mask%20R-CNN%20ax17_4%20iccv17.pdf),
[arxiv](https://arxiv.org/abs/1703.06870),
[code (keras)](https://github.com/matterport/Mask_RCNN),
[code (tensorflow)](https://github.com/CharlesShang/FastMaskRCNN))
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([pdf](video_detection/rnn/Context%20Matters%20Refining%20Object%20Detection%20in%20Video%20with%20Recurrent%20Neural%20Networks%20bmvc16.pdf),
[notes](video_detection/notes/Context%20Matters%20Refining%20Object%20Detection%20in%20Video%20with%20Recurrent%20Neural%20Networks%20bmvc16.pdf))



## Multi Object Tracking
- **Learning to Track: Online Multi-object Tracking by Decision Making**
(ICCV 2015) (Stanford)
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([pdf](single_object_tracking/rl/End-to-end%20Active%20Object%20Tracking%20via%20Reinforcement%20Learning%20ax17_5.pdf),
[arxiv](https://arxiv.org/abs/1705.10561))

## Other potentially useful papers
## Interpolation
- **Learning Features by Watching Objects Move**
(CVPR 2017)
([pdf(cvpr17)](unsupervised/segmentation/Learning%20Features%20by%20Watching%20Objects%20Move%20ax170412%20cvpr17.pdf),
[ppt](unsupervised/notes/Learning%20Features%20by%20Watching%20Objects%20Move%20ax170412%20cvpr17.pdf))

## Deep Learning
- **Do Deep Nets Really Need to be Deep**
(NIPS 2014)
([pdf](dl/theory/Do%20Deep%20Nets%20Really%20Need%20to%20be%20Deep%20ax1410%20nips14.pdf),
[notes](dl/notes/Do%20Deep%20Nets%20Really%20Need%20to%20be%20Deep%20ax1410%20nips14.pdf))

- Synthetic Gradients
- **Decoupled Neural Interfaces using Synthetic Gradients**
(arxiv August 2016)
([pdf](dl/synthetic_gradients/Decoupled%20Neural%20Interfaces%20using%20Synthetic%20Gradients%20ax1608.05343.pdf),
[notes](dl/notes/Decoupled%20Neural%20Interfaces%20using%20Synthetic%20Gradients%20ax1608.05343.pdf))

- **Understanding Synthetic Gradients and Decoupled Neural Interfaces**
(arxiv March 2017)
([pdf](dl/synthetic_gradients/Understanding%20Synthetic%20Gradients%20and%20Decoupled%20Neural%20Interfaces%20ax1703.00522.pdf),
[notes](multi_object_tracking/notes/Understanding%20Synthetic%20Gradients%20and%20Decoupled%20Neural%20Interfaces%20ax1703.00522.pdf))

## Unsupervised Learning
- **Video Frame Interpolation via Adaptive Convolution**
(CVPR 2017 / ICCV 2017)
([pdf(cvpr17)](interpolation/Video%20Frame%20Interpolation%20via%20Adaptive%20Convolution%20ax1703.pdf),
([pdf(iccv17)](interpolation/Video%20Frame%20Interpolation%20via%20Adaptive%20Separable%20Convolution%20iccv17.pdf),
[ppt](interpolation/notes/Video%20Frame%20Interpolation%20via%20Adaptive%20Convolution%20ax1703.pdf))

## Datasets
- [IDOT dataset](https://www.cs.uic.edu/Bits/YanziJin)
- [UA-DETRAC Benchmark Suite](http://detrac-db.rit.albany.edu/)
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