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Mask Region based Convolution Neural Networks – EXPLAINED!

Artis Modus



CodeEmporium

In this video, we will take a look at new type of neural network architecture called “Masked Region based Convolution Neural Networks”, Masked R-CNN for short. And in the process, highlight some key sub problems in computer vision.

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REFERENCES

Main paper: https://arxiv.org/pdf/1703.06870v3.pdf
Code: https://github.com/facebookresearch/Detectron

Convolution Neural networks: https://www.youtube.com/watch?v=m8pOnJxOcqY
Semantic segmentation in deep learning: http://blog.qure.ai/notes/semantic-segmentation-deep-learning-review
Top papers: http://www.arxiv-sanity.com/top?timefilter=alltime&vfilter=all
Recurrent Instance Segmentation: http://www.robots.ox.ac.uk/~tvg/publications/2016/RIS7.pdf
Mask R-CNN Presentation by the Author: https://www.youtube.com/watch?v=g7z4mkfRjI4
Mark Jay’s Video: https://www.youtube.com/watch?v=2TikTv6PWDw
COCO dataset: http://cocodataset.org/#home
Fully Convolutional Networks: https://people.eecs.berkeley.edu/~jonlong/long_shelhamer_fcn.pdf
Faster R-CNN explained: https://medium.com/@smallfishbigsea/faster-r-cnn-explained-864d4fb7e3f8
Notes/summary of Masked R-CNN: http://www.shortscience.org/paper?bibtexKey=journals/corr/HeGDG17#aleju

Music at : https://www.bensound.com/royalty-free-music/track/tenderness

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37 thoughts on “Mask Region based Convolution Neural Networks – EXPLAINED!”

  14. Great video and explanation. I used the model to detect lanes in roads using the Culanes Dataset with very good results. The project is in Github by the name RMASK_Lane_Detection

  22. At first thank you very much for this video. Your videos quality are very good. I have started to watch your videos. Can you
    Using Mask RCNN we can detect human class, from that human class can we detect human face ? Then which algorithm will i use to detect face ? Can you please give me some suggestions. And is it possible to use same dataset for human detection along with face detection ??

  31. If i want to use pretrained R-CNN for my own dataset to segment ( delineate) background from foerground , do i need to annotated or label my data ? The data i am using if person image ..

  36. Thank you for taking the time and efforts to make this video.
    Side note: the creepy whispered "subscribe" at the end of the video has more of a repulsive effect and doesn't really make me want to subscribe (more like making me want to close the video as fast as possible). The positive energy given during the video would probably work a lot better if it were used to ask for subscription too.

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