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https://github.com/osmr/imgclsmob

Sandbox for training deep learning networks
https://github.com/osmr/imgclsmob
3d-face-reconstruction chainer cifar classification deep-learning gluon human-pose-estimation image-classification imagenet keras machine-learning mxnet neural-network pretrained-models pytorch segmentation semantic-segmentation tensorflow tensorflow2
Last synced: 26 days ago
JSON representation
Sandbox for training deep learning networks
Host: GitHub
URL: https://github.com/osmr/imgclsmob
Owner: osmr
License: mit
Created: 2018-07-09T12:57:46.000Z (over 6 years ago)
Default Branch: master
Last Pushed: 2024-05-07T14:40:21.000Z (6 months ago)
Last Synced: 2024-05-17T21:03:04.675Z (6 months ago)
Topics: 3d-face-reconstruction, chainer, cifar, classification, deep-learning, gluon, human-pose-estimation, image-classification, imagenet, keras, machine-learning, mxnet, neural-network, pretrained-models, pytorch, segmentation, semantic-segmentation, tensorflow, tensorflow2
Language: Python
Homepage:
Size: 16.4 MB
Stars: 2,925
Watchers: 76
Forks: 559
Open Issues: 13
Metadata Files:
- Readme: README.md
- License: LICENSE
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README

        # Deep learning networks

[![Build Status](https://travis-ci.org/osmr/imgclsmob.svg?branch=master)](https://travis-ci.org/osmr/imgclsmob)

[![GitHub License](https://img.shields.io/badge/License-MIT-blue.svg)](https://opensource.org/licenses/MIT)

[![Python Version](https://img.shields.io/badge/python-3.10-lightgrey.svg)](https://github.com/osmr/imgclsmob)

This repo is used to research convolutional networks primarily for computer vision tasks. For this purpose, the repo

contains (re)implementations of various classification, segmentation, detection, and pose estimation models and scripts

for training/evaluating/converting.

The following frameworks are used:

- MXNet/Gluon ([info](https://mxnet.apache.org)),

- PyTorch ([info](https://pytorch.org)),

- Chainer ([info](https://chainer.org)),

- Keras ([info](https://keras.io)),

- TensorFlow 1.x/2.x ([info](https://www.tensorflow.org)).

For each supported framework, there is a PIP-package containing pure models without auxiliary scripts. List of packages:

- [gluoncv2](https://pypi.org/project/gluoncv2) for Gluon,

- [pytorchcv](https://pypi.org/project/pytorchcv) for PyTorch,

- [chainercv2](https://pypi.org/project/chainercv2) for Chainer,

- [kerascv](https://pypi.org/project/kerascv) for Keras,

- [tensorflowcv](https://pypi.org/project/tensorflowcv) for TensorFlow 1.x,

- [tf2cv](https://pypi.org/project/tf2cv) for TensorFlow 2.x.

Currently, models are mostly implemented on Gluon and then ported to other frameworks. Some models are pretrained on

[ImageNet-1K](http://www.image-net.org), [CIFAR-10/100](https://www.cs.toronto.edu/~kriz/cifar.html),

[SVHN](http://ufldl.stanford.edu/housenumbers), [CUB-200-2011](http://www.vision.caltech.edu/visipedia/CUB-200-2011.html),

[Pascal VOC2012](http://host.robots.ox.ac.uk/pascal/VOC/voc2012), [ADE20K](http://groups.csail.mit.edu/vision/datasets/ADE20K),

[Cityscapes](https://www.cityscapes-dataset.com), and [COCO](http://cocodataset.org) datasets. All pretrained weights

are loaded automatically during use. See examples of such automatic loading of weights in the corresponding sections of

the documentation dedicated to a particular package:

- [Gluon models](gluon/README.md),

- [PyTorch models](https://github.com/osmr/pytorchcv/blob/master/README.md),

- [Chainer models](chainer_/README.md),

- [Keras models](keras_/README.md),

- [TensorFlow 1.x models](tensorflow_/README.md),

- [TensorFlow 2.x models](tensorflow2/README.md).

## Installation

To use training/evaluating scripts as well as all models, you need to clone the repository and install dependencies:

```

git clone [email protected]:osmr/imgclsmob.git

pip install -r requirements.txt

```

## Table of implemented classification models

Some remarks:

- `Repo` is an author repository, if it exists.

- `a`, `b`, `c`, `d`, and `e` means the implementation of a model for ImageNet-1K, CIFAR-10, CIFAR-100, SVHN, and CUB-200-2011, respectively.

- `A`, `B`, `C`, `D`, and `E` means having a pre-trained model for corresponding datasets.

| Model | [Gluon](gluon/README.md) | [PyTorch](https://github.com/osmr/pytorchcv/blob/master/README.md) | [Chainer](chainer_/README.md) | [Keras](keras_/README.md) | [TF](tensorflow_/README.md) | [TF2](tensorflow2/README.md) | Paper | Repo | Year |

| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |

| AlexNet | A | A | A | A | A | A | [link](http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf) | [link](https://code.google.com/archive/p/cuda-convnet2) | 2012 |

| ZFNet | A | A | A | A | A | A | [link](https://arxiv.org/abs/1311.2901) | - | 2013 |

| VGG | A | A | A | A | A | A | [link](https://arxiv.org/abs/1409.1556) | - | 2014 |

| BN-VGG | A | A | A | A | A | A | [link](https://arxiv.org/abs/1409.1556) | - | 2015 |

| BN-Inception | A | A | A | - | - | A | [link](https://arxiv.org/abs/1502.03167) | - | 2015 |

| ResNet | ABCDE | ABCDE | ABCDE | A | A | ABCDE | [link](https://arxiv.org/abs/1512.03385) | [link](https://github.com/KaimingHe/deep-residual-networks) | 2015 |

| PreResNet | ABCD | ABCD | ABCD | A | A | ABCD | [link](https://arxiv.org/abs/1603.05027) | [link](https://github.com/facebook/fb.resnet.torch) | 2016 |

| ResNeXt | ABCD | ABCD | ABCD | A | A | ABCD | [link](http://arxiv.org/abs/1611.05431) | [link](https://github.com/facebookresearch/ResNeXt) | 2016 |

| SENet | A | A | A | A | A | A | [link](https://arxiv.org/abs/1709.01507) | [link](https://github.com/hujie-frank/SENet) | 2017 |

| SE-ResNet | ABCDE | ABCDE | ABCDE | A | A | ABCDE | [link](https://arxiv.org/abs/1709.01507) | [link](https://github.com/hujie-frank/SENet) | 2017 |

| SE-PreResNet | ABCD | ABCD | ABCD | A | A | ABCD | [link](https://arxiv.org/abs/1709.01507) | [link](https://github.com/hujie-frank/SENet) | 2017 |

| SE-ResNeXt | A | A | A | A | A | A | [link](https://arxiv.org/abs/1709.01507) | [link](https://github.com/hujie-frank/SENet) | 2017 |

| ResNeSt(A) | A | A | A | - | - | A | [link](https://arxiv.org/abs/2004.08955) | [link](https://github.com/zhanghang1989/ResNeSt) | 2020 |

| IBN-ResNet | A | A | - | - | - | A | [link](https://arxiv.org/abs/1807.09441) | [link](https://github.com/XingangPan/IBN-Net) | 2018 |

| IBN-ResNeXt | A | A | - | - | - | A | [link](https://arxiv.org/abs/1807.09441) | [link](https://github.com/XingangPan/IBN-Net) | 2018 |

| IBN-DenseNet | A | A | - | - | - | A | [link](https://arxiv.org/abs/1807.09441) | [link](https://github.com/XingangPan/IBN-Net) | 2018 |

| AirNet | A | A | A | - | - | A | [link](https://ieeexplore.ieee.org/document/8510896) | [link](https://github.com/soeaver/AirNet-PyTorch) | 2018 |

| AirNeXt | A | A | A | - | - | A | [link](https://ieeexplore.ieee.org/document/8510896) | [link](https://github.com/soeaver/AirNet-PyTorch) | 2018 |

| BAM-ResNet | A | A | A | - | - | A | [link](https://arxiv.org/abs/1807.06514) | [link](https://github.com/Jongchan/attention-module) | 2018 |

| CBAM-ResNet | A | A | A | - | - | A | [link](https://arxiv.org/abs/1807.06521) | [link](https://github.com/Jongchan/attention-module) | 2018 |

| ResAttNet | a | a | a | - | - | - | [link](https://arxiv.org/abs/1704.06904) | [link](https://github.com/fwang91/residual-attention-network) | 2017 |

| SKNet | a | a | a | - | - | - | [link](https://arxiv.org/abs/1903.06586) | [link](https://github.com/implus/SKNet) | 2019 |

| SCNet | A | A | A | - | - | A | [link](http://mftp.mmcheng.net/Papers/20cvprSCNet.pdf) | [link](https://github.com/MCG-NKU/SCNet) | 2020 |

| RegNet | A | A | A | - | - | A | [link](https://arxiv.org/abs/2003.13678) | [link](https://github.com/facebookresearch/pycls) | 2020 |

| DIA-ResNet | aBCD | aBCD | aBCD | - | - | - | [link](https://arxiv.org/abs/1905.10671) | [link](https://github.com/gbup-group/DIANet) | 2019 |

| DIA-PreResNet | aBCD | aBCD | aBCD | - | - | - | [link](https://arxiv.org/abs/1905.10671) | [link](https://github.com/gbup-group/DIANet) | 2019 |

| PyramidNet | ABCD | ABCD | ABCD | - | - | ABCD | [link](https://arxiv.org/abs/1610.02915) | [link](https://github.com/jhkim89/PyramidNet) | 2016 |

| DiracNetV2 | A | A | A | - | - | A | [link](https://arxiv.org/abs/1706.00388) | [link](https://github.com/szagoruyko/diracnets) | 2017 |

| ShaResNet | a | a | a | - | - | - | [link](https://arxiv.org/abs/1702.08782) | [link](https://github.com/aboulch/sharesnet) | 2017 |

| CRU-Net | A | - | - | - | - | - | [link](https://www.ijcai.org/proceedings/2018/88) | [link](https://github.com/cypw/CRU-Net) | 2018 |

| DenseNet | ABCD | ABCD | ABCD | A | A | ABCD | [link](https://arxiv.org/abs/1608.06993) | [link](https://github.com/liuzhuang13/DenseNet) | 2016 |

| CondenseNet | A | A | A | - | - | - | [link](https://arxiv.org/abs/1711.09224) | [link](https://github.com/ShichenLiu/CondenseNet) | 2017 |

| SparseNet | a | a | a | - | - | - | [link](https://arxiv.org/abs/1801.05895) | [link](https://github.com/Lyken17/SparseNet) | 2018 |

| PeleeNet | A | A | A | - | - | A | [link](https://arxiv.org/abs/1804.06882) | [link](https://github.com/Robert-JunWang/Pelee) | 2018 |

| Oct-ResNet | abcd | a | a | - | - | - | [link](https://arxiv.org/abs/1904.05049) | - | 2019 |

| Res2Net | a | - | - | - | - | - | [link](https://arxiv.org/abs/1904.01169) | - | 2019 |

| WRN | ABCD | ABCD | ABCD | - | - | a | [link](https://arxiv.org/abs/1605.07146) | [link](https://github.com/szagoruyko/wide-residual-networks) | 2016 |

| WRN-1bit | BCD | BCD | BCD | - | - | - | [link](https://arxiv.org/abs/1802.08530) | [link](https://github.com/McDonnell-Lab/1-bit-per-weight) | 2018 |

| DRN-C | A | A | A | - | - | A | [link](https://arxiv.org/abs/1705.09914) | [link](https://github.com/fyu/drn) | 2017 |

| DRN-D | A | A | A | - | - | A | [link](https://arxiv.org/abs/1705.09914) | [link](https://github.com/fyu/drn) | 2017 |

| DPN | A | A | A | - | - | A | [link](https://arxiv.org/abs/1707.01629) | [link](https://github.com/cypw/DPNs) | 2017 |

| DarkNet Ref | A | A | A | A | A | A | [link](https://github.com/pjreddie/darknet) | [link](https://github.com/pjreddie/darknet) | - |

| DarkNet Tiny | A | A | A | A | A | A | [link](https://github.com/pjreddie/darknet) | [link](https://github.com/pjreddie/darknet) | - |

| DarkNet-19 | a | a | a | a | a | a | [link](https://github.com/pjreddie/darknet) | [link](https://github.com/pjreddie/darknet) | - |

| DarkNet-53 | A | A | A | A | A | A | [link](https://arxiv.org/abs/1804.02767) | [link](https://github.com/pjreddie/darknet) | 2018 |

| ChannelNet | a | a | a | - | a | - | [link](https://arxiv.org/abs/1809.01330) | [link](https://github.com/HongyangGao/ChannelNets) | 2018 |

| iSQRT-COV-ResNet | a | a | - | - | - | - | [link](https://arxiv.org/abs/1712.01034) | [link](https://github.com/jiangtaoxie/fast-MPN-COV) | 2017 |

| RevNet | - | a | - | - | - | - | [link](https://arxiv.org/abs/1707.04585) | [link](https://github.com/renmengye/revnet-public) | 2017 |

| i-RevNet | A | A | A | - | - | - | [link](https://arxiv.org/abs/1802.07088) | [link](https://github.com/jhjacobsen/pytorch-i-revnet) | 2018 |

| BagNet | A | A | A | - | - | A | [link](https://openreview.net/pdf?id=SkfMWhAqYQ) | [link](https://github.com/wielandbrendel/bag-of-local-features-models) | 2019 |

| DLA | A | A | A | - | - | A | [link](https://arxiv.org/abs/1707.06484) | [link](https://github.com/ucbdrive/dla) | 2017 |

| MSDNet | a | ab | - | - | - | - | [link](https://arxiv.org/abs/1703.09844) | [link](https://github.com/gaohuang/MSDNet) | 2017 |

| FishNet | A | A | A | - | - | - | [link](http://papers.nips.cc/paper/7356-fishnet-a-versatile-backbone-for-image-region-and-pixel-level-prediction.pdf) | [link](https://github.com/kevin-ssy/FishNet) | 2018 |

| ESPNetv2 | A | A | A | - | - | - | [link](https://arxiv.org/abs/1811.11431) | [link](https://github.com/sacmehta/ESPNetv2) | 2018 |

| DiCENet | A | A | A | - | - | A | [link](https://arxiv.org/abs/1906.03516) | [link](https://github.com/sacmehta/EdgeNets) | 2019 |

| HRNet | A | A | A | - | - | A | [link](https://arxiv.org/abs/1908.07919) | [link](https://github.com/HRNet/HRNet-Image-Classification) | 2019 |

| VoVNet | A | A | A | - | - | A | [link](https://arxiv.org/abs/1904.09730) | [link](https://github.com/stigma0617/VoVNet.pytorch) | 2019 |

| SelecSLS | A | A | A | - | - | A | [link](https://arxiv.org/abs/1907.00837) | [link](https://github.com/mehtadushy/SelecSLS-Pytorch) | 2019 |

| HarDNet | A | A | A | - | - | A | [link](https://arxiv.org/abs/1909.00948) | [link](https://github.com/PingoLH/Pytorch-HarDNet) | 2019 |

| X-DenseNet | aBCD | aBCD | aBCD | - | - | - | [link](https://arxiv.org/abs/1711.08757) | [link](https://github.com/DrImpossible/Deep-Expander-Networks) | 2017 |

| SqueezeNet | A | A | A | A | A | A | [link](https://arxiv.org/abs/1602.07360) | [link](https://github.com/DeepScale/SqueezeNet) | 2016 |

| SqueezeResNet | A | A | A | A | A | A | [link](https://arxiv.org/abs/1602.07360) | - | 2016 |

| SqueezeNext | A | A | A | A | A | A | [link](https://arxiv.org/abs/1803.10615) | [link](https://github.com/amirgholami/SqueezeNext) | 2018 |

| ShuffleNet | A | A | A | A | A | A | [link](https://arxiv.org/abs/1707.01083) | - | 2017 |

| ShuffleNetV2 | A | A | A | A | A | A | [link](https://arxiv.org/abs/1807.11164) | - | 2018 |

| MENet | A | A | A | A | A | A | [link](https://arxiv.org/abs/1803.09127) | [link](https://github.com/clavichord93/MENet) | 2018 |

| MobileNet | AE | AE | AE | A | A | AE | [link](https://arxiv.org/abs/1704.04861) | [link](https://github.com/tensorflow/models) | 2017 |

| FD-MobileNet | A | A | A | A | A | A | [link](https://arxiv.org/abs/1802.03750) | [link](https://github.com/clavichord93/FD-MobileNet) | 2018 |

| MobileNetV2 | A | A | A | A | A | A | [link](https://arxiv.org/abs/1801.04381) | [link](https://github.com/tensorflow/models) | 2018 |

| MobileNetV3 | A | A | A | A | - | A | [link](https://arxiv.org/abs/1905.02244) | [link](https://github.com/tensorflow/models) | 2019 |

| IGCV3 | A | A | A | A | A | A | [link](https://arxiv.org/abs/1806.00178) | [link](https://github.com/homles11/IGCV3) | 2018 |

| GhostNet | a | a | a | - | - | a | [link](https://arxiv.org/abs/1911.11907) | [link](https://github.com/iamhankai/ghostnet) | 2019 |

| MnasNet | A | A | A | A | A | A | [link](https://arxiv.org/abs/1807.11626) | - | 2018 |

| DARTS | A | A | A | - | - | - | [link](https://arxiv.org/abs/1806.09055) | [link](https://github.com/quark0/darts) | 2018 |

| ProxylessNAS | AE | AE | AE | - | - | AE | [link](https://arxiv.org/abs/1812.00332) | [link](https://github.com/mit-han-lab/ProxylessNAS) | 2018 |

| FBNet-C | A | A | A | - | - | A | [link](https://arxiv.org/abs/1812.03443) | - | 2018 |

| Xception | A | A | A | - | - | A | [link](https://arxiv.org/abs/1610.02357) | [link](https://github.com/fchollet/deep-learning-models) | 2016 |

| InceptionV3 | A | A | A | - | - | A | [link](https://arxiv.org/abs/1512.00567) | [link](https://github.com/tensorflow/models) | 2015 |

| InceptionV4 | A | A | A | - | - | A | [link](https://arxiv.org/abs/1602.07261) | [link](https://github.com/tensorflow/models) | 2016 |

| InceptionResNetV1 | A | A | A | - | - | A | [link](https://arxiv.org/abs/1602.07261) | [link](https://github.com/tensorflow/models) | 2016 |

| InceptionResNetV2 | A | A | A | - | - | A | [link](https://arxiv.org/abs/1602.07261) | [link](https://github.com/tensorflow/models) | 2016 |

| PolyNet | A | A | A | - | - | A | [link](https://arxiv.org/abs/1611.05725) | [link](https://github.com/open-mmlab/polynet) | 2016 |

| NASNet-Large | A | A | A | - | - | A | [link](https://arxiv.org/abs/1707.07012) | [link](https://github.com/tensorflow/models) | 2017 |

| NASNet-Mobile | A | A | A | - | - | A | [link](https://arxiv.org/abs/1707.07012) | [link](https://github.com/tensorflow/models) | 2017 |

| PNASNet-Large | A | A | A | - | - | A | [link](https://arxiv.org/abs/1712.00559) | [link](https://github.com/tensorflow/models) | 2017 |

| SPNASNet | A | A | A | - | - | A | [link](https://arxiv.org/abs/1904.02877) | [link](https://github.com/dstamoulis/single-path-nas) | 2019 |

| EfficientNet | A | A | A | A | - | A | [link](https://arxiv.org/abs/1905.11946) | [link](https://github.com/tensorflow/tpu/tree/master/models/official/efficientnet) | 2019 |

| MixNet | A | A | A | - | - | A | [link](https://arxiv.org/abs/1907.09595) | [link](https://github.com/tensorflow/tpu/tree/master/models/official/mnasnet/mixnet) | 2019 |

| NIN | BCD | BCD | BCD | - | - | - | [link](https://arxiv.org/abs/1312.4400) | [link](https://gist.github.com/mavenlin/e56253735ef32c3c296d) | 2013 |

| RoR-3 | BCD | BCD | BCD | - | - | - | [link](https://arxiv.org/abs/1608.02908) | - | 2016 |

| RiR | BCD | BCD | BCD | - | - | - | [link](https://arxiv.org/abs/1603.08029) | - | 2016 |

| ResDrop-ResNet | bcd | bcd | bcd | - | - | - | [link](https://arxiv.org/abs/1603.09382) | [link](https://github.com/yueatsprograms/Stochastic_Depth) | 2016 |

| Shake-Shake-ResNet | BCD | BCD | BCD | - | - | - | [link](https://arxiv.org/abs/1705.07485) | [link](https://github.com/xgastaldi/shake-shake) | 2017 |

| ShakeDrop-ResNet | bcd | bcd | bcd | - | - | - | [link](https://arxiv.org/abs/1802.02375) | - | 2018 |

| FractalNet | bc | bc | - | - | - | - | [link](https://arxiv.org/abs/1605.07648) | [link](https://github.com/gustavla/fractalnet) | 2016 |

| NTS-Net | E | E | E | - | - | - | [link](https://arxiv.org/abs/1809.00287) | [link](https://github.com/yangze0930/NTS-Net) | 2018 |

## Table of implemented segmentation models

Some remarks:

- `a/A` corresponds to Pascal VOC2012.

- `b/B` corresponds to ADE20K.

- `c/C` corresponds to Cityscapes.

- `d/D` corresponds to COCO.

- `e/E` corresponds to CelebAMask-HQ.

| Model | [Gluon](gluon/README.md) | [PyTorch](https://github.com/osmr/pytorchcv/blob/master/README.md) | [Chainer](chainer_/README.md) | [Keras](keras_/README.md) | [TF](tensorflow_/README.md)  | [TF2](tensorflow_/README.md) | Paper | Repo | Year |

| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |

| PSPNet | ABCD | ABCD | ABCD | - | - | ABCD | [link](https://arxiv.org/abs/1612.01105) | - | 2016 |

| DeepLabv3 | ABcD | ABcD | ABcD | - | - | ABcD | [link](https://arxiv.org/abs/1706.05587) | - | 2017 |

| FCN-8s(d) | ABcD | ABcD | ABcD | - | - | ABcD | [link](https://arxiv.org/abs/1411.4038) | - | 2014 |

| ICNet | C | C | C | - | - | C | [link](https://arxiv.org/abs/1704.08545) | [link](https://github.com/hszhao/ICNet) | 2017 |

| SINet | C | C | C | - | - | c | [link](https://arxiv.org/abs/1911.09099) | [link](https://github.com/clovaai/c3_sinet) | 2019 |

| BiSeNet | e | e | e | - | - | e | [link](https://arxiv.org/abs/1808.00897) | - | 2018 |

| DANet | C | C | C | - | - | C | [link](https://arxiv.org/abs/1809.02983) | [link](https://github.com/junfu1115/DANet) | 2018 |

| Fast-SCNN | C | C | C | - | - | C | [link](https://arxiv.org/abs/1902.04502) | - | 2019 |

| CGNet | c | c | c | - | - | c | [link](https://arxiv.org/abs/1811.08201) | [link](https://github.com/wutianyiRosun/CGNet) | 2018 |

| DABNet | c | c | c | - | - | c | [link](https://arxiv.org/abs/1907.11357) | [link](https://github.com/Reagan1311/DABNet) | 2019 |

| FPENet | c | c | c | - | - | c | [link](https://arxiv.org/abs/1909.08599) | - | 2019 |

| ContextNet | - | c | - | - | - | - | [link](https://arxiv.org/abs/1805.04554) | - | 2018 |

| LEDNet | c | c | c | - | - | c | [link](https://arxiv.org/abs/1905.02423) | - | 2019 |

| ESNet | - | c | - | - | - | - | [link](https://arxiv.org/abs/1906.09826) | - | 2019 |

| EDANet | - | c | - | - | - | - | [link](https://arxiv.org/abs/1809.06323) | [link](https://github.com/shaoyuanlo/EDANet) | 2018 |

| ENet | - | c | - | - | - | - | [link](https://arxiv.org/abs/1606.02147) | - | 2016 |

| ERFNet | - | c | - | - | - | - | [link](http://www.robesafe.uah.es/personal/eduardo.romera/pdfs/Romera17tits.pdf) | - | 2017 |

| LinkNet | - | c | - | - | - | - | [link](https://arxiv.org/abs/1707.03718) | - | 2017 |

| SegNet | - | c | - | - | - | - | [link](https://arxiv.org/abs/1511.00561) | - | 2015 |

| U-Net | - | c | - | - | - | - | [link](https://arxiv.org/abs/1505.04597) | - | 2015 |

| SQNet | - | c | - | - | - | - | [link](https://openreview.net/pdf?id=S1uHiFyyg) | - | 2016 |

## Table of implemented object detection models

Some remarks:

- `a/A` corresponds to COCO.

| Model | [Gluon](gluon/README.md) | [PyTorch](https://github.com/osmr/pytorchcv/blob/master/README.md) | [Chainer](chainer_/README.md) | [Keras](keras_/README.md) | [TF](tensorflow_/README.md)  | [TF2](tensorflow2/README.md) | Paper | Repo | Year |

| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |

| CenterNet | a | a | a | - | - | a | [link](https://arxiv.org/abs/1904.07850) | [link](https://github.com/xingyizhou/CenterNet) | 2019 |

## Table of implemented human pose estimation models

Some remarks:

- `a/A` corresponds to COCO.

| Model | [Gluon](gluon/README.md) | [PyTorch](https://github.com/osmr/pytorchcv/blob/master/README.md) | [Chainer](chainer_/README.md) | [Keras](keras_/README.md) | [TF](tensorflow_/README.md)  | [TF2](tensorflow2/README.md) | Paper | Repo | Year |

| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |

| AlphaPose | A | A | A | - | - | A | [link](https://arxiv.org/abs/1612.00137) | [link](https://github.com/MVIG-SJTU/AlphaPose) | 2016 |

| SimplePose | A | A | A | - | - | A | [link](https://arxiv.org/abs/1804.06208) | [link](https://github.com/microsoft/human-pose-estimation.pytorch) | 2018 |

| SimplePose(Mobile) | A | A | A | - | - | A | [link](https://arxiv.org/abs/1804.06208) | - | 2018 |

| Lightweight OpenPose | A | A | A | - | - | A | [link](https://arxiv.org/abs/1811.12004) | [link](https://github.com/Daniil-Osokin/lightweight-human-pose-estimation-3d-demo.pytorch) | 2018 |

| IBPPose | A | A | A | - | - | A | [link](https://arxiv.org/abs/1911.10529) | [link](https://github.com/jialee93/Improved-Body-Parts) | 2019 |

## Table of implemented automatic speech recognition models

Some remarks:

- `a/A` corresponds to LibriSpeech.

- `b/B` corresponds to Mozilla Common Voice.

| Model | [Gluon](gluon/README.md) | [PyTorch](https://github.com/osmr/pytorchcv/blob/master/README.md) | [Chainer](chainer_/README.md) | [Keras](keras_/README.md) | [TF](tensorflow_/README.md)  | [TF2](tensorflow2/README.md) | Paper | Repo | Year |

| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |

| Jasper DR | AB | AB | ab | - | - | ab | [link](https://arxiv.org/abs/1904.03288) | [link](https://github.com/NVIDIA/NeMo) | 2019 |

| QuartzNet | AB | AB | ab | - | - | ab | [link](https://arxiv.org/abs/1910.10261) | [link](https://github.com/NVIDIA/NeMo) | 2019 |