deep learning for image processing including classification and object-detection etc.
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Updated
Jan 12, 2025 - Python
deep learning for image processing including classification and object-detection etc.
BoxMOT: Pluggable SOTA multi-object tracking modules modules for segmentation, object detection and pose estimation models
Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.
Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125
Pytorch implementation of convolutional neural network visualization techniques
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
Mask RCNN in TensorFlow
All-in-One Development Tool based on PaddlePaddle
Segmentation models with pretrained backbones. Keras and TensorFlow Keras.
PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
Semantic Segmentation Suite in TensorFlow. Implement, train, and test new Semantic Segmentation models easily!
The OCR approach is rephrased as Segmentation Transformer: https://arxiv.org/abs/1909.11065. This is an official implementation of semantic segmentation for HRNet. https://arxiv.org/abs/1908.07919
《深度学习与计算机视觉》配套代码
Caffe models (including classification, detection and segmentation) and deploy files for famouse networks
Sandbox for training deep learning networks
[IEEE TMI] Official Implementation for UNet++
A pytorch implementation of Detectron. Both training from scratch and inferring directly from pretrained Detectron weights are available.
a generalist algorithm for cellular segmentation with human-in-the-loop capabilities
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