{"id":13444141,"url":"https://github.com/osmr/imgclsmob","last_synced_at":"2025-05-14T05:10:45.472Z","repository":{"id":39988109,"uuid":"140285687","full_name":"osmr/imgclsmob","owner":"osmr","description":"Sandbox for training deep learning networks","archived":false,"fork":false,"pushed_at":"2024-09-06T09:38:46.000Z","size":16338,"stargazers_count":3007,"open_issues_count":13,"forks_count":561,"subscribers_count":76,"default_branch":"master","last_synced_at":"2025-05-09T07:21:35.102Z","etag":null,"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"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/osmr.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2018-07-09T12:57:46.000Z","updated_at":"2025-05-09T03:32:19.000Z","dependencies_parsed_at":"2024-05-06T11:56:53.682Z","dependency_job_id":"53d3d1b3-1858-4f7a-baae-98e4ca1b00f2","html_url":"https://github.com/osmr/imgclsmob","commit_stats":{"total_commits":2517,"total_committers":3,"mean_commits":839.0,"dds":0.0007945967421533195,"last_synced_commit":"c1a844dde061f6d72f25011dc1af9a2e35b1bdfc"},"previous_names":[],"tags_count":570,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/osmr%2Fimgclsmob","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/osmr%2Fimgclsmob/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/osmr%2Fimgclsmob/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/osmr%2Fimgclsmob/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/osmr","download_url":"https://codeload.github.com/osmr/imgclsmob/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":254076850,"owners_count":22010611,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["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"],"created_at":"2024-07-31T03:02:20.134Z","updated_at":"2025-05-14T05:10:45.446Z","avatar_url":"https://github.com/osmr.png","language":"Python","funding_links":[],"categories":["Python","Uncategorized","Preferred Networks Research","\u003ca name=\"Vision\"\u003e\u003c/a\u003e2. Vision","Pytorch \u0026 related libraries｜Pytorch \u0026 相关库","Pytorch \u0026 related libraries","Model Deployment library","Tutorials \u0026 Examples","Examples/Notebooks"],"sub_categories":["Uncategorized","Computer Vision","2.1 Image Classification","CV｜计算机视觉:","CV:","PyTorch \u003ca name=\"pytorch\"/\u003e"],"readme":"# Deep learning networks\n\n[![Build Status](https://travis-ci.org/osmr/imgclsmob.svg?branch=master)](https://travis-ci.org/osmr/imgclsmob)\n[![GitHub License](https://img.shields.io/badge/License-MIT-blue.svg)](https://opensource.org/licenses/MIT)\n[![Python Version](https://img.shields.io/badge/python-3.10-lightgrey.svg)](https://github.com/osmr/imgclsmob)\n\nThis repo is used to research convolutional networks primarily for computer vision tasks. For this purpose, the repo\ncontains (re)implementations of various classification, segmentation, detection, and pose estimation models and scripts\nfor training/evaluating/converting.\n\nThe following frameworks are used:\n- MXNet/Gluon ([info](https://mxnet.apache.org)),\n- PyTorch ([info](https://pytorch.org)),\n- Chainer ([info](https://chainer.org)),\n- Keras ([info](https://keras.io)),\n- TensorFlow 1.x/2.x ([info](https://www.tensorflow.org)).\n\nFor each supported framework, there is a PIP-package containing pure models without auxiliary scripts. List of packages:\n- [gluoncv2](https://pypi.org/project/gluoncv2) for Gluon,\n- [pytorchcv](https://pypi.org/project/pytorchcv) for PyTorch,\n- [chainercv2](https://pypi.org/project/chainercv2) for Chainer,\n- [kerascv](https://pypi.org/project/kerascv) for Keras,\n- [tensorflowcv](https://pypi.org/project/tensorflowcv) for TensorFlow 1.x,\n- [tf2cv](https://pypi.org/project/tf2cv) for TensorFlow 2.x.\n\nCurrently, models are mostly implemented on Gluon and then ported to other frameworks. Some models are pretrained on\n[ImageNet-1K](http://www.image-net.org), [CIFAR-10/100](https://www.cs.toronto.edu/~kriz/cifar.html),\n[SVHN](http://ufldl.stanford.edu/housenumbers), [CUB-200-2011](http://www.vision.caltech.edu/visipedia/CUB-200-2011.html),\n[Pascal VOC2012](http://host.robots.ox.ac.uk/pascal/VOC/voc2012), [ADE20K](http://groups.csail.mit.edu/vision/datasets/ADE20K),\n[Cityscapes](https://www.cityscapes-dataset.com), and [COCO](http://cocodataset.org) datasets. All pretrained weights\nare loaded automatically during use. See examples of such automatic loading of weights in the corresponding sections of\nthe documentation dedicated to a particular package:\n- [Gluon models](gluon/README.md),\n- [PyTorch models](https://github.com/osmr/pytorchcv/blob/master/README.md),\n- [Chainer models](chainer_/README.md),\n- [Keras models](keras_/README.md),\n- [TensorFlow 1.x models](tensorflow_/README.md),\n- [TensorFlow 2.x models](tensorflow2/README.md).\n\n## Installation\n\nTo use training/evaluating scripts as well as all models, you need to clone the repository and install dependencies:\n```\ngit clone git@github.com:osmr/imgclsmob.git\npip install -r requirements.txt\n```\n\n## Table of implemented classification models\n\nSome remarks:\n- `Repo` is an author repository, if it exists.\n- `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.\n- `A`, `B`, `C`, `D`, and `E` means having a pre-trained model for corresponding datasets.\n\n| 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 |\n| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |\n| 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 |\n| ZFNet | A | A | A | A | A | A | [link](https://arxiv.org/abs/1311.2901) | - | 2013 |\n| VGG | A | A | A | A | A | A | [link](https://arxiv.org/abs/1409.1556) | - | 2014 |\n| BN-VGG | A | A | A | A | A | A | [link](https://arxiv.org/abs/1409.1556) | - | 2015 |\n| BN-Inception | A | A | A | - | - | A | [link](https://arxiv.org/abs/1502.03167) | - | 2015 |\n| ResNet | ABCDE | ABCDE | ABCDE | A | A | ABCDE | [link](https://arxiv.org/abs/1512.03385) | [link](https://github.com/KaimingHe/deep-residual-networks) | 2015 |\n| PreResNet | ABCD | ABCD | ABCD | A | A | ABCD | [link](https://arxiv.org/abs/1603.05027) | [link](https://github.com/facebook/fb.resnet.torch) | 2016 |\n| ResNeXt | ABCD | ABCD | ABCD | A | A | ABCD | [link](http://arxiv.org/abs/1611.05431) | [link](https://github.com/facebookresearch/ResNeXt) | 2016 |\n| SENet | A | A | A | A | A | A | [link](https://arxiv.org/abs/1709.01507) | [link](https://github.com/hujie-frank/SENet) | 2017 |\n| SE-ResNet | ABCDE | ABCDE | ABCDE | A | A | ABCDE | [link](https://arxiv.org/abs/1709.01507) | [link](https://github.com/hujie-frank/SENet) | 2017 |\n| SE-PreResNet | ABCD | ABCD | ABCD | A | A | ABCD | [link](https://arxiv.org/abs/1709.01507) | [link](https://github.com/hujie-frank/SENet) | 2017 |\n| SE-ResNeXt | A | A | A | A | A | A | [link](https://arxiv.org/abs/1709.01507) | [link](https://github.com/hujie-frank/SENet) | 2017 |\n| ResNeSt(A) | A | A | A | - | - | A | [link](https://arxiv.org/abs/2004.08955) | [link](https://github.com/zhanghang1989/ResNeSt) | 2020 |\n| IBN-ResNet | A | A | - | - | - | A | [link](https://arxiv.org/abs/1807.09441) | [link](https://github.com/XingangPan/IBN-Net) | 2018 |\n| IBN-ResNeXt | A | A | - | - | - | A | [link](https://arxiv.org/abs/1807.09441) | [link](https://github.com/XingangPan/IBN-Net) | 2018 |\n| IBN-DenseNet | A | A | - | - | - | A | [link](https://arxiv.org/abs/1807.09441) | [link](https://github.com/XingangPan/IBN-Net) | 2018 |\n| AirNet | A | A | A | - | - | A | [link](https://ieeexplore.ieee.org/document/8510896) | [link](https://github.com/soeaver/AirNet-PyTorch) | 2018 |\n| AirNeXt | A | A | A | - | - | A | [link](https://ieeexplore.ieee.org/document/8510896) | [link](https://github.com/soeaver/AirNet-PyTorch) | 2018 |\n| BAM-ResNet | A | A | A | - | - | A | [link](https://arxiv.org/abs/1807.06514) | [link](https://github.com/Jongchan/attention-module) | 2018 |\n| CBAM-ResNet | A | A | A | - | - | A | [link](https://arxiv.org/abs/1807.06521) | [link](https://github.com/Jongchan/attention-module) | 2018 |\n| ResAttNet | a | a | a | - | - | - | [link](https://arxiv.org/abs/1704.06904) | [link](https://github.com/fwang91/residual-attention-network) | 2017 |\n| SKNet | a | a | a | - | - | - | [link](https://arxiv.org/abs/1903.06586) | [link](https://github.com/implus/SKNet) | 2019 |\n| SCNet | A | A | A | - | - | A | [link](http://mftp.mmcheng.net/Papers/20cvprSCNet.pdf) | [link](https://github.com/MCG-NKU/SCNet) | 2020 |\n| RegNet | A | A | A | - | - | A | [link](https://arxiv.org/abs/2003.13678) | [link](https://github.com/facebookresearch/pycls) | 2020 |\n| DIA-ResNet | aBCD | aBCD | aBCD | - | - | - | [link](https://arxiv.org/abs/1905.10671) | [link](https://github.com/gbup-group/DIANet) | 2019 |\n| DIA-PreResNet | aBCD | aBCD | aBCD | - | - | - | [link](https://arxiv.org/abs/1905.10671) | [link](https://github.com/gbup-group/DIANet) | 2019 |\n| PyramidNet | ABCD | ABCD | ABCD | - | - | ABCD | [link](https://arxiv.org/abs/1610.02915) | [link](https://github.com/jhkim89/PyramidNet) | 2016 |\n| DiracNetV2 | A | A | A | - | - | A | [link](https://arxiv.org/abs/1706.00388) | [link](https://github.com/szagoruyko/diracnets) | 2017 |\n| ShaResNet | a | a | a | - | - | - | [link](https://arxiv.org/abs/1702.08782) | [link](https://github.com/aboulch/sharesnet) | 2017 |\n| CRU-Net | A | - | - | - | - | - | [link](https://www.ijcai.org/proceedings/2018/88) | [link](https://github.com/cypw/CRU-Net) | 2018 |\n| DenseNet | ABCD | ABCD | ABCD | A | A | ABCD | [link](https://arxiv.org/abs/1608.06993) | [link](https://github.com/liuzhuang13/DenseNet) | 2016 |\n| CondenseNet | A | A | A | - | - | - | [link](https://arxiv.org/abs/1711.09224) | [link](https://github.com/ShichenLiu/CondenseNet) | 2017 |\n| SparseNet | a | a | a | - | - | - | [link](https://arxiv.org/abs/1801.05895) | [link](https://github.com/Lyken17/SparseNet) | 2018 |\n| PeleeNet | A | A | A | - | - | A | [link](https://arxiv.org/abs/1804.06882) | [link](https://github.com/Robert-JunWang/Pelee) | 2018 |\n| Oct-ResNet | abcd | a | a | - | - | - | [link](https://arxiv.org/abs/1904.05049) | - | 2019 |\n| Res2Net | a | - | - | - | - | - | [link](https://arxiv.org/abs/1904.01169) | - | 2019 |\n| WRN | ABCD | ABCD | ABCD | - | - | a | [link](https://arxiv.org/abs/1605.07146) | [link](https://github.com/szagoruyko/wide-residual-networks) | 2016 |\n| WRN-1bit | BCD | BCD | BCD | - | - | - | [link](https://arxiv.org/abs/1802.08530) | [link](https://github.com/McDonnell-Lab/1-bit-per-weight) | 2018 |\n| DRN-C | A | A | A | - | - | A | [link](https://arxiv.org/abs/1705.09914) | [link](https://github.com/fyu/drn) | 2017 |\n| DRN-D | A | A | A | - | - | A | [link](https://arxiv.org/abs/1705.09914) | [link](https://github.com/fyu/drn) | 2017 |\n| DPN | A | A | A | - | - | A | [link](https://arxiv.org/abs/1707.01629) | [link](https://github.com/cypw/DPNs) | 2017 |\n| DarkNet Ref | A | A | A | A | A | A | [link](https://github.com/pjreddie/darknet) | [link](https://github.com/pjreddie/darknet) | - |\n| DarkNet Tiny | A | A | A | A | A | A | [link](https://github.com/pjreddie/darknet) | [link](https://github.com/pjreddie/darknet) | - |\n| DarkNet-19 | a | a | a | a | a | a | [link](https://github.com/pjreddie/darknet) | [link](https://github.com/pjreddie/darknet) | - |\n| DarkNet-53 | A | A | A | A | A | A | [link](https://arxiv.org/abs/1804.02767) | [link](https://github.com/pjreddie/darknet) | 2018 |\n| ChannelNet | a | a | a | - | a | - | [link](https://arxiv.org/abs/1809.01330) | [link](https://github.com/HongyangGao/ChannelNets) | 2018 |\n| iSQRT-COV-ResNet | a | a | - | - | - | - | [link](https://arxiv.org/abs/1712.01034) | [link](https://github.com/jiangtaoxie/fast-MPN-COV) | 2017 |\n| RevNet | - | a | - | - | - | - | [link](https://arxiv.org/abs/1707.04585) | [link](https://github.com/renmengye/revnet-public) | 2017 |\n| i-RevNet | A | A | A | - | - | - | [link](https://arxiv.org/abs/1802.07088) | [link](https://github.com/jhjacobsen/pytorch-i-revnet) | 2018 |\n| BagNet | A | A | A | - | - | A | [link](https://openreview.net/pdf?id=SkfMWhAqYQ) | [link](https://github.com/wielandbrendel/bag-of-local-features-models) | 2019 |\n| DLA | A | A | A | - | - | A | [link](https://arxiv.org/abs/1707.06484) | [link](https://github.com/ucbdrive/dla) | 2017 |\n| MSDNet | a | ab | - | - | - | - | [link](https://arxiv.org/abs/1703.09844) | [link](https://github.com/gaohuang/MSDNet) | 2017 |\n| 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 |\n| ESPNetv2 | A | A | A | - | - | - | [link](https://arxiv.org/abs/1811.11431) | [link](https://github.com/sacmehta/ESPNetv2) | 2018 |\n| DiCENet | A | A | A | - | - | A | [link](https://arxiv.org/abs/1906.03516) | [link](https://github.com/sacmehta/EdgeNets) | 2019 |\n| HRNet | A | A | A | - | - | A | [link](https://arxiv.org/abs/1908.07919) | [link](https://github.com/HRNet/HRNet-Image-Classification) | 2019 |\n| VoVNet | A | A | A | - | - | A | [link](https://arxiv.org/abs/1904.09730) | [link](https://github.com/stigma0617/VoVNet.pytorch) | 2019 |\n| SelecSLS | A | A | A | - | - | A | [link](https://arxiv.org/abs/1907.00837) | [link](https://github.com/mehtadushy/SelecSLS-Pytorch) | 2019 |\n| HarDNet | A | A | A | - | - | A | [link](https://arxiv.org/abs/1909.00948) | [link](https://github.com/PingoLH/Pytorch-HarDNet) | 2019 |\n| X-DenseNet | aBCD | aBCD | aBCD | - | - | - | [link](https://arxiv.org/abs/1711.08757) | [link](https://github.com/DrImpossible/Deep-Expander-Networks) | 2017 |\n| SqueezeNet | A | A | A | A | A | A | [link](https://arxiv.org/abs/1602.07360) | [link](https://github.com/DeepScale/SqueezeNet) | 2016 |\n| SqueezeResNet | A | A | A | A | A | A | [link](https://arxiv.org/abs/1602.07360) | - | 2016 |\n| SqueezeNext | A | A | A | A | A | A | [link](https://arxiv.org/abs/1803.10615) | [link](https://github.com/amirgholami/SqueezeNext) | 2018 |\n| ShuffleNet | A | A | A | A | A | A | [link](https://arxiv.org/abs/1707.01083) | - | 2017 |\n| ShuffleNetV2 | A | A | A | A | A | A | [link](https://arxiv.org/abs/1807.11164) | - | 2018 |\n| MENet | A | A | A | A | A | A | [link](https://arxiv.org/abs/1803.09127) | [link](https://github.com/clavichord93/MENet) | 2018 |\n| MobileNet | AE | AE | AE | A | A | AE | [link](https://arxiv.org/abs/1704.04861) | [link](https://github.com/tensorflow/models) | 2017 |\n| FD-MobileNet | A | A | A | A | A | A | [link](https://arxiv.org/abs/1802.03750) | [link](https://github.com/clavichord93/FD-MobileNet) | 2018 |\n| MobileNetV2 | A | A | A | A | A | A | [link](https://arxiv.org/abs/1801.04381) | [link](https://github.com/tensorflow/models) | 2018 |\n| MobileNetV3 | A | A | A | A | - | A | [link](https://arxiv.org/abs/1905.02244) | [link](https://github.com/tensorflow/models) | 2019 |\n| IGCV3 | A | A | A | A | A | A | [link](https://arxiv.org/abs/1806.00178) | [link](https://github.com/homles11/IGCV3) | 2018 |\n| GhostNet | a | a | a | - | - | a | [link](https://arxiv.org/abs/1911.11907) | [link](https://github.com/iamhankai/ghostnet) | 2019 |\n| MnasNet | A | A | A | A | A | A | [link](https://arxiv.org/abs/1807.11626) | - | 2018 |\n| DARTS | A | A | A | - | - | - | [link](https://arxiv.org/abs/1806.09055) | [link](https://github.com/quark0/darts) | 2018 |\n| ProxylessNAS | AE | AE | AE | - | - | AE | [link](https://arxiv.org/abs/1812.00332) | [link](https://github.com/mit-han-lab/ProxylessNAS) | 2018 |\n| FBNet-C | A | A | A | - | - | A | [link](https://arxiv.org/abs/1812.03443) | - | 2018 |\n| Xception | A | A | A | - | - | A | [link](https://arxiv.org/abs/1610.02357) | [link](https://github.com/fchollet/deep-learning-models) | 2016 |\n| InceptionV3 | A | A | A | - | - | A | [link](https://arxiv.org/abs/1512.00567) | [link](https://github.com/tensorflow/models) | 2015 |\n| InceptionV4 | A | A | A | - | - | A | [link](https://arxiv.org/abs/1602.07261) | [link](https://github.com/tensorflow/models) | 2016 |\n| InceptionResNetV1 | A | A | A | - | - | A | [link](https://arxiv.org/abs/1602.07261) | [link](https://github.com/tensorflow/models) | 2016 |\n| InceptionResNetV2 | A | A | A | - | - | A | [link](https://arxiv.org/abs/1602.07261) | [link](https://github.com/tensorflow/models) | 2016 |\n| PolyNet | A | A | A | - | - | A | [link](https://arxiv.org/abs/1611.05725) | [link](https://github.com/open-mmlab/polynet) | 2016 |\n| NASNet-Large | A | A | A | - | - | A | [link](https://arxiv.org/abs/1707.07012) | [link](https://github.com/tensorflow/models) | 2017 |\n| NASNet-Mobile | A | A | A | - | - | A | [link](https://arxiv.org/abs/1707.07012) | [link](https://github.com/tensorflow/models) | 2017 |\n| PNASNet-Large | A | A | A | - | - | A | [link](https://arxiv.org/abs/1712.00559) | [link](https://github.com/tensorflow/models) | 2017 |\n| SPNASNet | A | A | A | - | - | A | [link](https://arxiv.org/abs/1904.02877) | [link](https://github.com/dstamoulis/single-path-nas) | 2019 |\n| 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 |\n| 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 |\n| NIN | BCD | BCD | BCD | - | - | - | [link](https://arxiv.org/abs/1312.4400) | [link](https://gist.github.com/mavenlin/e56253735ef32c3c296d) | 2013 |\n| RoR-3 | BCD | BCD | BCD | - | - | - | [link](https://arxiv.org/abs/1608.02908) | - | 2016 |\n| RiR | BCD | BCD | BCD | - | - | - | [link](https://arxiv.org/abs/1603.08029) | - | 2016 |\n| ResDrop-ResNet | bcd | bcd | bcd | - | - | - | [link](https://arxiv.org/abs/1603.09382) | [link](https://github.com/yueatsprograms/Stochastic_Depth) | 2016 |\n| Shake-Shake-ResNet | BCD | BCD | BCD | - | - | - | [link](https://arxiv.org/abs/1705.07485) | [link](https://github.com/xgastaldi/shake-shake) | 2017 |\n| ShakeDrop-ResNet | bcd | bcd | bcd | - | - | - | [link](https://arxiv.org/abs/1802.02375) | - | 2018 |\n| FractalNet | bc | bc | - | - | - | - | [link](https://arxiv.org/abs/1605.07648) | [link](https://github.com/gustavla/fractalnet) | 2016 |\n| NTS-Net | E | E | E | - | - | - | [link](https://arxiv.org/abs/1809.00287) | [link](https://github.com/yangze0930/NTS-Net) | 2018 |\n\n## Table of implemented segmentation models\n\nSome remarks:\n- `a/A` corresponds to Pascal VOC2012.\n- `b/B` corresponds to ADE20K.\n- `c/C` corresponds to Cityscapes.\n- `d/D` corresponds to COCO.\n- `e/E` corresponds to CelebAMask-HQ.\n\n| 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 |\n| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |\n| PSPNet | ABCD | ABCD | ABCD | - | - | ABCD | [link](https://arxiv.org/abs/1612.01105) | - | 2016 |\n| DeepLabv3 | ABcD | ABcD | ABcD | - | - | ABcD | [link](https://arxiv.org/abs/1706.05587) | - | 2017 |\n| FCN-8s(d) | ABcD | ABcD | ABcD | - | - | ABcD | [link](https://arxiv.org/abs/1411.4038) | - | 2014 |\n| ICNet | C | C | C | - | - | C | [link](https://arxiv.org/abs/1704.08545) | [link](https://github.com/hszhao/ICNet) | 2017 |\n| SINet | C | C | C | - | - | c | [link](https://arxiv.org/abs/1911.09099) | [link](https://github.com/clovaai/c3_sinet) | 2019 |\n| BiSeNet | e | e | e | - | - | e | [link](https://arxiv.org/abs/1808.00897) | - | 2018 |\n| DANet | C | C | C | - | - | C | [link](https://arxiv.org/abs/1809.02983) | [link](https://github.com/junfu1115/DANet) | 2018 |\n| Fast-SCNN | C | C | C | - | - | C | [link](https://arxiv.org/abs/1902.04502) | - | 2019 |\n| CGNet | c | c | c | - | - | c | [link](https://arxiv.org/abs/1811.08201) | [link](https://github.com/wutianyiRosun/CGNet) | 2018 |\n| DABNet | c | c | c | - | - | c | [link](https://arxiv.org/abs/1907.11357) | [link](https://github.com/Reagan1311/DABNet) | 2019 |\n| FPENet | c | c | c | - | - | c | [link](https://arxiv.org/abs/1909.08599) | - | 2019 |\n| ContextNet | - | c | - | - | - | - | [link](https://arxiv.org/abs/1805.04554) | - | 2018 |\n| LEDNet | c | c | c | - | - | c | [link](https://arxiv.org/abs/1905.02423) | - | 2019 |\n| ESNet | - | c | - | - | - | - | [link](https://arxiv.org/abs/1906.09826) | - | 2019 |\n| EDANet | - | c | - | - | - | - | [link](https://arxiv.org/abs/1809.06323) | [link](https://github.com/shaoyuanlo/EDANet) | 2018 |\n| ENet | - | c | - | - | - | - | [link](https://arxiv.org/abs/1606.02147) | - | 2016 |\n| ERFNet | - | c | - | - | - | - | [link](http://www.robesafe.uah.es/personal/eduardo.romera/pdfs/Romera17tits.pdf) | - | 2017 |\n| LinkNet | - | c | - | - | - | - | [link](https://arxiv.org/abs/1707.03718) | - | 2017 |\n| SegNet | - | c | - | - | - | - | [link](https://arxiv.org/abs/1511.00561) | - | 2015 |\n| U-Net | - | c | - | - | - | - | [link](https://arxiv.org/abs/1505.04597) | - | 2015 |\n| SQNet | - | c | - | - | - | - | [link](https://openreview.net/pdf?id=S1uHiFyyg) | - | 2016 |\n\n## Table of implemented object detection models\n\nSome remarks:\n- `a/A` corresponds to COCO.\n\n| 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 |\n| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |\n| CenterNet | a | a | a | - | - | a | [link](https://arxiv.org/abs/1904.07850) | [link](https://github.com/xingyizhou/CenterNet) | 2019 |\n\n## Table of implemented human pose estimation models\n\nSome remarks:\n- `a/A` corresponds to COCO.\n\n| 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 |\n| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |\n| AlphaPose | A | A | A | - | - | A | [link](https://arxiv.org/abs/1612.00137) | [link](https://github.com/MVIG-SJTU/AlphaPose) | 2016 |\n| SimplePose | A | A | A | - | - | A | [link](https://arxiv.org/abs/1804.06208) | [link](https://github.com/microsoft/human-pose-estimation.pytorch) | 2018 |\n| SimplePose(Mobile) | A | A | A | - | - | A | [link](https://arxiv.org/abs/1804.06208) | - | 2018 |\n| 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 |\n| IBPPose | A | A | A | - | - | A | [link](https://arxiv.org/abs/1911.10529) | [link](https://github.com/jialee93/Improved-Body-Parts) | 2019 |\n\n## Table of implemented automatic speech recognition models\n\nSome remarks:\n- `a/A` corresponds to LibriSpeech.\n- `b/B` corresponds to Mozilla Common Voice.\n\n| 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 |\n| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |\n| Jasper DR | AB | AB | ab | - | - | ab | [link](https://arxiv.org/abs/1904.03288) | [link](https://github.com/NVIDIA/NeMo) | 2019 |\n| QuartzNet | AB | AB | ab | - | - | ab | [link](https://arxiv.org/abs/1910.10261) | [link](https://github.com/NVIDIA/NeMo) | 2019 |\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fosmr%2Fimgclsmob","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fosmr%2Fimgclsmob","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fosmr%2Fimgclsmob/lists"}