x2ss's repositories
Awesome-pytorch-list
A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.
Deformable-Convolution-V2-PyTorch
Deformable ConvNets V2 in PyTorch
FPN_Tensorflow-1
This is a tensorflow re-implementation of Feature Pyramid Networks for Object Detection.
keras-global-context-networks
Keras implementation of Global Context Attention blocks
pretrained-models.pytorch
Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.
Reproducible-Deep-Compressive-Sensing
Collection of reproducible deep learning for compressive sensing
segmentation_models
Segmentation models with pretrained backbones. Keras.
Tensorflow-Unet
U-Net implementation in TensorFlow for image segmentation(multi class and Resnet50 backbone)
BEVFusion
Offical PyTorch implementation of "BEVFusion: A Simple and Robust LiDAR-Camera Fusion Framework"
center_loss_classification
Implementation resnet and center-loss in Tensorflow
computervision-recipes
Best Practices, code samples, and documentation for Computer Vision.
GANimation
GANimation: Anatomically-aware Facial Animation from a Single Image (ECCV'18 Oral) [PyTorch]
Meta-SR-Pytorch
Meta-SR: A Magnification-Arbitrary Network for Super-Resolution (CVPR2019)
mmdetection
Open MMLab Detection Toolbox and Benchmark
Monocular-Depth-Estimation-Toolbox
Monocular Depth Estimation Toolbox based on MMSegmentation.
multispectral-object-detection
Multispectral Object Detection with Yolov5 and Transformer
prepare_detection_dataset
convert dataset to coco/voc format
Semantic-Segmentation-Suite
Semantic Segmentation Suite in TensorFlow. Implement, train, and test new Semantic Segmentation models easily!
Slow-Fast-pytorch-implementation
Action recognition using Slow Fast Network by FAIR
SlowFast-Network-pytorch
An easy PyTorch implement of SlowFast-Network
stanford_alpaca
Code and documentation to train Stanford's Alpaca models, and generate the data.
unifiedparsing
Codebase and pretrained models for ECCV'18 Unified Perceptual Parsing