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PyTorch implementation of MAE https//arxiv.org/abs/2111.06377
Unofficial PyTorch implementation of Masked Autoencoders Are Scalable Vision Learners
Polyp-PVT: Polyp Segmentation with Pyramid Vision Transformers, AIR 2023.
Official PyTorch Implementation of Hypercorrelation Squeeze for Few-Shot Segmentation, ICCV 2021
ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual-Inertial and Multi-Map SLAM
Real-Time SLAM for Monocular, Stereo and RGB-D Cameras, with Loop Detection and Relocalization Capabilities
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
🤘 awesome-semantic-segmentation
🎨 Semantic segmentation models, datasets and losses implemented in PyTorch.
Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.
deep learning for image processing including classification and object-detection etc.
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
implementation of paper - You Only Learn One Representation: Unified Network for Multiple Tasks (https://arxiv.org/abs/2105.04206)
YOLOv3 in PyTorch > ONNX > CoreML > TFLite
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…
YOLOv4/v5, clean code, good performance,easy to understand.