图像与视频处理算法汇总（代码）

目录

一、文本检测（定位）

二、目标检测

三、行为识别

四、Visual Relationship Detection

五、语义分割

五、实例分割

六、超分辨率

七、显著目标检测salient object detection

八、开源的图像处理库

九、数据集

---

一、文本检测（定位）

https://github.com/hwalsuklee/awesome-deep-text-detection-recognition

https://github.com/clovaai/CRAFT-pytorch （CVPR19）

百度PaddleOCR：https://github.com/PaddlePaddle/PaddleOCR/blob/develop/README_ch.md

二、目标检测

• 综述： https://github.com/hoya012/deep_learning_object_detection
• 综述： https://github.com/amusi/awesome-object-detection
• 目标检测API： https://github.com/Stick-To/Object-Detection-API-Tensorflow
• Efficientdet (CVPR2020) : https://github.com/google/automl/tree/master/efficientdet
• Efficientdet (CVPR2020) : https://github.com/zylo117/Yet-Another-EfficientDet-Pytorch
• Efficientdet水下目标检测： https://github.com/DataXujing/EfficientDet_pytorch
• faster rcnn : https://github.com/ruotianluo/pytorch-faster-rcnn (pytorch)
• SSD: https://github.com/amdegroot/ssd.pytorch (pytorch)
• Refinedet：https://github.com/luuuyi/RefineDet.PyTorch (pytorch)
• M2Det: https://github.com/qijiezhao/M2Det
• 水下图像目标检测SWIPENet：https://github.com/LongChenCV/SWIPENet

 

基于anchor free的方法：

CornerNet： https://github.com/princeton-vl/CornerNet

 

三、行为识别

• 综述： https://github.com/jinwchoi/awesome-action-recognition
• 综述： https://github.com/jinwchoi/awesome-action-recognition
• slowfast（官方）：https://github.com/facebookresearch/SlowFast
• slowfast: https://github.com/anhminh3105/SlowFast
• two-stream-action-recognition：https://github.com/mohammed-elkomy/two-stream-action-recognition
• Video Platform for Recognition and Detection in Pytorch （VIP）：https://github.com/MichiganCOG/ViP
• 3DCNN： https://github.com/dipakkr/3d-cnn-action-recognition

 

四、Visual Relationship Detection

matranse: https://github.com/deeplab-ai/matranse

待补充。。。

 

五、语义分割

1、U-Net:

• https://github.com/zhixuhao/unet [Keras]
• https://github.com/jocicmarko/ultrasound-nerve-segmentation [Keras]
• https://github.com/EdwardTyantov/ultrasound-nerve-segmentation [Keras]
• https://github.com/ZFTurbo/ZF_UNET_224_Pretrained_Model [Keras]
• https://github.com/yihui-he/u-net [Keras]
• https://github.com/jakeret/tf_unet [Tensorflow]
• https://github.com/divamgupta/image-segmentation-keras [Keras]
• https://github.com/ZijunDeng/pytorch-semantic-segmentation [PyTorch]
• https://github.com/akirasosa/mobile-semantic-segmentation [Keras]
• https://github.com/orobix/retina-unet [Keras]
• https://github.com/qureai/ultrasound-nerve-segmentation-using-torchnet [Torch]
• https://github.com/ternaus/TernausNet [PyTorch]
• https://github.com/qubvel/segmentation_models [Keras]
• https://github.com/LeeJunHyun/Image_Segmentation#u-net [PyTorch]
• https://github.com/yassouali/pytorch_segmentation [PyTorch]
• https://lmb.informatik.uni-freiburg.de/people/ronneber/u-net/ [Caffe + Matlab]

2、SegNet:

•  [https://arxiv.org/pdf/1511.00561.pdf] [2016]

• https://github.com/alexgkendall/caffe-segnet [Caffe]

• https://github.com/developmentseed/caffe/tree/segnet-multi-gpu [Caffe]

• https://github.com/preddy5/segnet [Keras]

• https://github.com/imlab-uiip/keras-segnet [Keras]

• https://github.com/andreaazzini/segnet [Tensorflow]

• https://github.com/fedor-chervinskii/segnet-torch [Torch]

• https://github.com/0bserver07/Keras-SegNet-Basic [Keras]

• https://github.com/tkuanlun350/Tensorflow-SegNet [Tensorflow]

• https://github.com/divamgupta/image-segmentation-keras [Keras]

• https://github.com/ZijunDeng/pytorch-semantic-segmentation [PyTorch]

• https://github.com/chainer/chainercv/tree/master/examples/segnet [Chainer]

• https://github.com/ykamikawa/keras-SegNet [Keras]

• https://github.com/ykamikawa/tf-keras-SegNet [Keras]

• https://github.com/yassouali/pytorch_segmentation [PyTorch]

3、DeepLab:

• [https://arxiv.org/pdf/1606.00915.pdf] [2017]

• https://bitbucket.org/deeplab/deeplab-public/ [Caffe]

• https://github.com/cdmh/deeplab-public [Caffe]

• https://bitbucket.org/aquariusjay/deeplab-public-ver2 [Caffe]

• https://github.com/TheLegendAli/DeepLab-Context [Caffe]

• https://github.com/msracver/Deformable-ConvNets/tree/master/deeplab [MXNet]

• https://github.com/DrSleep/tensorflow-deeplab-resnet [Tensorflow]

• https://github.com/muyang0320/tensorflow-deeplab-resnet-crf [TensorFlow]

• https://github.com/isht7/pytorch-deeplab-resnet [PyTorch]

• https://github.com/bermanmaxim/jaccardSegment [PyTorch]

• https://github.com/martinkersner/train-DeepLab [Caffe]

• https://github.com/chenxi116/TF-deeplab [Tensorflow]

• https://github.com/bonlime/keras-deeplab-v3-plus [Keras]

• https://github.com/tensorflow/models/tree/master/research/deeplab [Tensorflow]

• https://github.com/speedinghzl/pytorch-segmentation-toolbox [PyTorch]

• https://github.com/kazuto1011/deeplab-pytorch [PyTorch]

• https://github.com/youansheng/torchcv [PyTorch]

• https://github.com/yassouali/pytorch_segmentation [PyTorch]

4、FCN :

• [https://arxiv.org/pdf/1605.06211.pdf] [2016]

• https://github.com/vlfeat/matconvnet-fcn [MatConvNet]

• https://github.com/shelhamer/fcn.berkeleyvision.org [Caffe]

• https://github.com/MarvinTeichmann/tensorflow-fcn [Tensorflow]

• https://github.com/aurora95/Keras-FCN [Keras]

• https://github.com/mzaradzki/neuralnets/tree/master/vgg_segmentation_keras [Keras]

• https://github.com/k3nt0w/FCN_via_keras [Keras]

• https://github.com/shekkizh/FCN.tensorflow [Tensorflow]

• https://github.com/seewalker/tf-pixelwise [Tensorflow]

• https://github.com/divamgupta/image-segmentation-keras [Keras]

• https://github.com/ZijunDeng/pytorch-semantic-segmentation [PyTorch]

• https://github.com/wkentaro/pytorch-fcn [PyTorch]

• https://github.com/wkentaro/fcn [Chainer]

• https://github.com/apache/incubator-mxnet/tree/master/example/fcn-xs [MxNet]

• https://github.com/muyang0320/tf-fcn [Tensorflow]

• https://github.com/ycszen/pytorch-seg [PyTorch]

• https://github.com/Kaixhin/FCN-semantic-segmentation [PyTorch]

• https://github.com/petrama/VGGSegmentation [Tensorflow]

• https://github.com/simonguist/testing-fcn-for-cityscapes [Caffe]

• https://github.com/hellochick/semantic-segmentation-tensorflow [Tensorflow]

• https://github.com/pierluigiferrari/fcn8s_tensorflow [Tensorflow]

• https://github.com/theduynguyen/Keras-FCN [Keras]

• https://github.com/JihongJu/keras-fcn [Keras]

• https://github.com/yassouali/pytorch_segmentation [PyTorch]

5、ENet :

• [https://arxiv.org/pdf/1606.02147.pdf] [2016]

• https://github.com/TimoSaemann/ENet [Caffe]

• https://github.com/e-lab/ENet-training [Torch]

• https://github.com/PavlosMelissinos/enet-keras [Keras]

• https://github.com/fregu856/segmentation [Tensorflow]

• https://github.com/kwotsin/TensorFlow-ENet [Tensorflow]

• https://github.com/davidtvs/PyTorch-ENet [PyTorch]

• https://github.com/yassouali/pytorch_segmentation [PyTorch]

6、LinkNet:

• [https://arxiv.org/pdf/1707.03718.pdf] [2017]

• https://github.com/e-lab/LinkNet [Torch]

• https://github.com/qubvel/segmentation_models [Keras]

7、DenseNet

• [https://arxiv.org/pdf/1611.09326.pdf] [2017]
  • https://github.com/SimJeg/FC-DenseNet [Lasagne]
  • https://github.com/HasnainRaz/FC-DenseNet-TensorFlow [Tensorflow]
  • https://github.com/0bserver07/One-Hundred-Layers-Tiramisu [Keras]

8、DilatedNet

• [https://arxiv.org/pdf/1511.07122.pdf] [2016]
  • https://github.com/nicolov/segmentation_keras [Keras]
  • https://github.com/fyu/dilation [Caffe]
  • https://github.com/fyu/drn#semantic-image-segmentataion [PyTorch]
  • https://github.com/hangzhaomit/semantic-segmentation-pytorch [PyTorch]

9、PixelNet

• [https://arxiv.org/pdf/1609.06694.pdf] [2016]
  • https://github.com/aayushbansal/PixelNet [Caffe]

10、ICNet

• [https://arxiv.org/pdf/1704.08545.pdf] [2017]

• https://github.com/hszhao/ICNet [Caffe]

• https://github.com/aitorzip/Keras-ICNet [Keras]

• https://github.com/hellochick/ICNet-tensorflow [Tensorflow]

• https://github.com/oandrienko/fast-semantic-segmentation [Tensorflow]

• https://github.com/supervisely/supervisely/tree/master/plugins/nn/icnet [PyTorch]

11、ERFNet

• [http://www.robesafe.uah.es/personal/eduardo.romera/pdfs/Romera17iv.pdf] [?]
  • https://github.com/Eromera/erfnet [Torch]
  • https://github.com/Eromera/erfnet_pytorch [PyTorch]

12、RefineNet

• [https://arxiv.org/pdf/1611.06612.pdf] [2016]
  • https://github.com/guosheng/refinenet [MatConvNet]

13、PSPNet

• [https://arxiv.org/pdf/1612.01105.pdf,https://hszhao.github.io/projects/pspnet/] [2017]

• https://github.com/hszhao/PSPNet [Caffe]

• https://github.com/ZijunDeng/pytorch-semantic-segmentation [PyTorch]

• https://github.com/mitmul/chainer-pspnet [Chainer]

• https://github.com/Vladkryvoruchko/PSPNet-Keras-tensorflow [Keras/Tensorflow]

• https://github.com/pudae/tensorflow-pspnet [Tensorflow]

• https://github.com/hellochick/PSPNet-tensorflow [Tensorflow]

• https://github.com/hellochick/semantic-segmentation-tensorflow [Tensorflow]

• https://github.com/qubvel/segmentation_models [Keras]

• https://github.com/oandrienko/fast-semantic-segmentation [Tensorflow]

• https://github.com/speedinghzl/pytorch-segmentation-toolbox [PyTorch]

• https://github.com/youansheng/torchcv [PyTorch]

• https://github.com/yassouali/pytorch_segmentation [PyTorch]

• https://github.com/holyseven/PSPNet-TF-Reproduce [Tensorflow]

• https://github.com/kazuto1011/pspnet-pytorch [PyTorch]

14、DeconvNet

• [https://arxiv.org/pdf/1505.04366.pdf] [2015]
• http://cvlab.postech.ac.kr/research/deconvnet/ [Caffe]
• https://github.com/HyeonwooNoh/DeconvNet [Caffe]
• https://github.com/fabianbormann/Tensorflow-DeconvNet-Segmentation [Tensorflow]

15、FRRN

• [https://arxiv.org/pdf/1611.08323.pdf] [2016]
• https://github.com/TobyPDE/FRRN [Lasagne]

16、GCN

• [https://arxiv.org/pdf/1703.02719.pdf] [2017]
• https://github.com/ZijunDeng/pytorch-semantic-segmentation [PyTorch]
• https://github.com/ycszen/pytorch-seg [PyTorch]
• https://github.com/yassouali/pytorch_segmentation [PyTorch]

17、LRR

• [https://arxiv.org/pdf/1605.02264.pdf] [2016]
• https://github.com/golnazghiasi/LRR [Matconvnet]

18、DUC, HDC

• [https://arxiv.org/pdf/1702.08502.pdf] [2017]
• https://github.com/ZijunDeng/pytorch-semantic-segmentation [PyTorch]
• https://github.com/ycszen/pytorch-seg [PyTorch]
• https://github.com/yassouali/pytorch_segmentation [PyTorch]

19、MultiNet

• [https://arxiv.org/pdf/1612.07695.pdf] [2016]
• https://github.com/MarvinTeichmann/MultiNet
• https://github.com/MarvinTeichmann/KittiSeg

20、Segaware

• [https://arxiv.org/pdf/1708.04607.pdf] [2017]
• https://github.com/aharley/segaware [Caffe]

21、Semantic Segmentation using Adversarial Networks 

• https://arxiv.org/pdf/1611.08408.pdf] [2016]
• https://github.com/oyam/Semantic-Segmentation-using-Adversarial-Networks [Chainer]

22、PixelDCN

• [https://arxiv.org/pdf/1705.06820.pdf] [2017]
• https://github.com/HongyangGao/PixelDCN [Tensorflow]

ShuffleSeg

• [https://arxiv.org/pdf/1803.03816.pdf] [2018]
• https://github.com/MSiam/TFSegmentation [TensorFlow]

23、AdaptSegNet

• [https://arxiv.org/pdf/1802.10349.pdf] [2018]
• https://github.com/wasidennis/AdaptSegNet [PyTorch]

24、TuSimple-DUC

• [https://arxiv.org/pdf/1702.08502.pdf] [2018]
• https://github.com/TuSimple/TuSimple-DUC [MxNet]

25、FPN

• [http://presentations.cocodataset.org/COCO17-Stuff-FAIR.pdf] [2017]
• https://github.com/qubvel/segmentation_models [Keras]

26、R2U-Net

• [https://arxiv.org/ftp/arxiv/papers/1802/1802.06955.pdf] [2018]
• https://github.com/LeeJunHyun/Image_Segmentation#r2u-net [PyTorch]

27、Attention U-Net

• [https://arxiv.org/pdf/1804.03999.pdf] [2018]
• https://github.com/LeeJunHyun/Image_Segmentation#attention-u-net [PyTorch]
• https://github.com/ozan-oktay/Attention-Gated-Networks [PyTorch]

28、DANet

• [https://arxiv.org/pdf/1809.02983.pdf] [2018]
• https://github.com/junfu1115/DANet [PyTorch]

29、ShelfNet

• [https://arxiv.org/pdf/1811.11254.pdf] [2018]
• https://github.com/juntang-zhuang/ShelfNet [PyTorch]

30、LadderNet

• [https://arxiv.org/pdf/1810.07810.pdf] [2018]
• https://github.com/juntang-zhuang/LadderNet [PyTorch]

31、BiSeNet

• [https://arxiv.org/pdf/1808.00897.pdf] [2018]
• https://github.com/ooooverflow/BiSeNet [PyTorch]
• https://github.com/ycszen/TorchSeg [PyTorch]
• https://github.com/zllrunning/face-parsing.PyTorch [PyTorch]

32、ESPNet

• [https://arxiv.org/pdf/1803.06815.pdf] [2018]
• https://github.com/sacmehta/ESPNet [PyTorch]

33、DFN

• [https://arxiv.org/pdf/1804.09337.pdf] [2018]
• https://github.com/ycszen/TorchSeg [PyTorch]

34、CCNet

• [https://arxiv.org/pdf/1811.11721.pdf] [2018]
• https://github.com/speedinghzl/CCNet [PyTorch]

35、DenseASPP

• [http://openaccess.thecvf.com/content_cvpr_2018/papers/Yang_DenseASPP_for_Semantic_CVPR_2018_paper.pdf] [2018]
• https://github.com/youansheng/torchcv [PyTorch]

36、Fast-SCNN

• [https://arxiv.org/pdf/1902.04502.pdf] [2019]
• https://github.com/DeepVoltaire/Fast-SCNN [PyTorch]

37、HRNet

• [https://arxiv.org/pdf/1904.04514.pdf] [2019]
• https://github.com/HRNet/HRNet-Semantic-Segmentation [PyTorch]

38、PSANet

• [https://hszhao.github.io/papers/eccv18_psanet.pdf] [2018]
• https://github.com/hszhao/PSANet [Caffe]

39、UPSNet

• [https://arxiv.org/pdf/1901.03784.pdf] [2019]
• https://github.com/uber-research/UPSNet [PyTorch]

40、ConvCRF

• [https://arxiv.org/pdf/1805.04777.pdf] [2018]
• https://github.com/MarvinTeichmann/ConvCRF [PyTorch]

41、Multi-scale Guided Attention for Medical Image Segmentation

• [https://arxiv.org/pdf/1906.02849.pdf] [2019]
• https://github.com/sinAshish/Multi-Scale-Attention [PyTorch]

42、DFANet

• [https://arxiv.org/pdf/1904.02216.pdf] [2019]
• https://github.com/huaifeng1993/DFANet [PyTorch]

43、ExtremeC3Net

• [https://arxiv.org/pdf/1908.03093.pdf] [2019]
• https://github.com/HYOJINPARK/ExtPortraitSeg [PyTorch]

44、EncNet

• [https://arxiv.org/pdf/1803.08904.pdf] [2018]
• https://github.com/zhanghang1989/PyTorch-Encoding [PyTorch]

45、Unet++：

• https://github.com/MrGiovanni/UNetPlusPlus [Keras]
• https://github.com/4uiiurz1/pytorch-nested-unet [PyTorch]

46、FastFCN：https://github.com/wuhuikai/FastFCN [PyTorch]

47、PortraitNet：https://github.com/dong-x16/PortraitNet [PyTorch]

五、实例分割

mask rcnn: https://github.com/matterport/Mask_RCNN (tensorflow)

mask rcnn: https://github.com/facebookresearch/maskrcnn-benchmark

FCIS(2017): https://github.com/msracver/FCIS

Deep Learning for Instance Segmentation of Agricultural Fields - Master thesis: https://github.com/chrieke/InstanceSegmentation_Sentinel2

PANet(2018): https://github.com/ShuLiu1993/PANet

polarMask: https://github.com/xieenze/PolarMask

SOLO(2020): https://github.com/WXinlong/SOLO

CenterMask(CVPR2020): https://github.com/youngwanLEE/CenterMask

PointRend: https://github.com/zsef123/PointRend-PyTorch

待补充。。

 

六、超分辨率

图像超分辨率：https://github.com/ChaofWang/Awesome-Super-Resolution

https://github.com/YingqianWang/Awesome-LF-Image-SR

 

视频超分辨率：https://github.com/wsz1029/Awesome-Video-Super-Resolution

待补充。。

 

七、显著目标检测salient object detection

综述：https://github.com/jiwei0921/SOD-CNNs-based-code-summary-

DSS(CVPR2017)：https://github.com/Joker316701882/Salient-Object-Detection

SalBenchmark（比较早的综述）：https://github.com/MCG-NKU/SalBenchmark

BSANet（CVPR9）：https://github.com/NathanUA/BASNet

EGNet（ICCV2019）：https://github.com/JXingZhao/EGNet

CPD（CVPR2019）：https://github.com/wuzhe71/CPD

PoolNet（CVPR2019）：https://github.com/backseason/PoolNet

 

视频显著目标检测：

ViSalientObject（TIP2018）：https://github.com/wenguanwang/ViSalientObject

PDB-ConvLSTM（ECCV8）：https://github.com/shenjianbing/PDB-ConvLSTM

MGA（ICCV9）：https://github.com/lhaof/Motion-Guided-Attention

 

 

 

八、开源的图像处理库

Detectron2:  https://github.com/facebookresearch/detectron2

mmdetection:  https://github.com/open-mmlab/mmdetection

pyimagesearch: https://www.pyimagesearch.com/books-and-courses/

 

九、数据集

COCO： https://cocodataset.org/#download

 

其它代码：

VOC数据转COC：https://github.com/shiyemin/voc2coco

 

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