https://github.com/byte7/deep-learning-papers-implementation
Implementing popular DL papers
https://github.com/byte7/deep-learning-papers-implementation
Last synced: about 2 months ago
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Implementing popular DL papers
- Host: GitHub
- URL: https://github.com/byte7/deep-learning-papers-implementation
- Owner: Byte7
- License: mit
- Created: 2018-12-11T16:53:35.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2018-12-25T05:37:37.000Z (over 6 years ago)
- Last Synced: 2025-01-31T01:34:45.307Z (4 months ago)
- Language: Jupyter Notebook
- Size: 14.7 MB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Deep-Learning-Papers-Implementation
Implementing popular DL papers
#### Architectures
- [X] AlexNet [`paper`](https://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks)
- [X] ZFNet [`paper`](https://arxiv.org/abs/1311.2901)
- [ ] VGG16 [`paper1`](https://arxiv.org/abs/1505.06798) [`paper2`](https://arxiv.org/pdf/1409.1556.pdf)
- [ ] ResNet [`paper`](https://arxiv.org/abs/1704.06904)
- [ ] GoogLeNet [`paper`](https://arxiv.org/abs/1409.4842)
- [ ] Inception [`paper`](https://arxiv.org/abs/1512.00567)
- [ ] Xception [`paper`](https://arxiv.org/abs/1610.02357)
- [ ] MobileNet [`paper`](https://arxiv.org/abs/1704.04861)
#### Semantic Segmentation
- [ ] FCN [`paper`](https://arxiv.org/abs/1411.4038)
- [ ] SegNet [`paper`](https://arxiv.org/abs/1511.00561)
- [ ] UNet [`paper`](https://arxiv.org/abs/1505.04597)
- [ ] PSPNet [`paper`](https://arxiv.org/abs/1612.01105)
- [ ] DeepLab [`paper`](https://arxiv.org/abs/1606.00915)
- [ ] ICNet [`paper`](https://arxiv.org/abs/1704.08545)
- [ ] ENet [`paper`](https://arxiv.org/abs/1606.02147)
#### Generative adversarial networks
- [X] GAN [`paper`](https://arxiv.org/abs/1406.2661)
- [X] DCGAN [`paper`](https://arxiv.org/abs/1511.06434)
- [ ] WGAN [`paper`](https://arxiv.org/abs/1701.07875)
- [ ] Pix2Pix [`paper`](https://arxiv.org/abs/1611.07004)
- [ ] CycleGAN [`paper`](https://arxiv.org/abs/1703.10593)
- [ ] Progressive GAN [`paper`](#)
#### Object detection
- [ ] RCNN [`paper`](https://arxiv.org/abs/1311.2524)
- [ ] Fast-RCNN [`paper`](https://arxiv.org/abs/1504.08083)
- [ ] Faster-RCNN [`paper`](https://arxiv.org/abs/1506.01497)
- [ ] SSD [`paper`](https://arxiv.org/abs/1512.02325)
- [ ] YOLO [`paper`](https://arxiv.org/abs/1506.02640)
- [ ] YOLO9000 [`paper`](https://arxiv.org/abs/1612.08242)