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.
Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125
Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.
Pytorch implementation of convolutional neural network visualization techniques
BoxMOT: pluggable SOTA tracking modules for segmentation, object detection and pose estimation models
All-in-One Development Tool based on PaddlePaddle
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
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
A Python package for segmenting geospatial data with the Segment Anything Model (SAM)
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
Mask RCNN in TensorFlow
A procedural Blender pipeline for photorealistic training image generation
Sandbox for training deep learning networks
Efficient vision foundation models for high-resolution generation and perception.
A pytorch implementation of Detectron. Both training from scratch and inferring directly from pretrained Detectron weights are available.
Papers and Datasets about Point Cloud.
Pytorch framework for doing deep learning on point clouds.
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