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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.
Tutorials, assignments, and competitions for MIT Deep Learning related courses.
Hello AI World guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson.
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.
Segment Anything in High Quality [NeurIPS 2023]
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
深度学习入门课、资深课、特色课、学术案例、产业实践案例、深度学习知识百科及面试题库The course, case and knowledge of Deep Learning and AI
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