Detectors
DetectoRS: Detecting Objects with Recursive Feature Pyramid and Switchable Atrous Convolution
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Detectors | 1,055 | 2 years ago | 47 | apache-2.0 | Python | |||||
| DetectoRS: Detecting Objects with Recursive Feature Pyramid and Switchable Atrous Convolution | ||||||||||
| Sepc | 325 | a year ago | 4 | apache-2.0 | Python | |||||
| Scale-equalizing Pyramid Convolution for object detection(CVPR2020) | ||||||||||
| Deeplab_pytorch | 75 | 6 years ago | 4 | mit | Python | |||||
| Repository for DeepLab family | ||||||||||
| Cv_papers | 68 | 3 years ago | 1 | mit | ||||||
| 计算机视觉方面的分类、对象检测、图像分割、人脸检测、OCR等中文翻译 | ||||||||||
| Deep_text_matching | 68 | 4 years ago | 1 | Python | ||||||
| implementation several deep text match (text similarly) models for keras . cdssm, arc-ii,match_pyramid, mvlstm ,esim, drcn ,bimpm, bert, albert, raberta | ||||||||||
| Segmentation Series Chaos | 43 | 4 years ago | apache-2.0 | |||||||
| Summary and experiment includes basic segmentation, human segmentation, human or portrait matting for both image and video. | ||||||||||
| Pypyrtools | 37 | a year ago | 4 | February 05, 2018 | 5 | mit | Jupyter Notebook | |||
| Python tools for multi-scale image processing, including Laplacian pyramids, Wavelets, and Steerable Pyramids http://www.cns.nyu.edu/~lcv/software.php | ||||||||||
| Tf_semanticsegmentation | 22 | 5 years ago | Python | |||||||
| Semantic image segmentation network with pyramid atrous convolution and boundary-aware loss for Tensorflow. | ||||||||||
| Pclnet | 21 | 5 years ago | 2 | mit | Python | |||||
| Unsupervised Learning for Optical Flow Estimation Using Pyramid Convolution LSTM. | ||||||||||
| Class_feature_visualization_pyramid | 14 | 4 years ago | mit | Python | ||||||
| PyTorch code for Class Visualization Pyramid for intpreting spatio-temporal class-specific activations throughout the network | ||||||||||
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