Swin-TransformerThis is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".
Stars: ✭ 8,046 (+61792.31%)
Mutual labels: imagenet, semantic-segmentation
Segmentation models.pytorchSegmentation models with pretrained backbones. PyTorch.
Stars: ✭ 4,584 (+35161.54%)
Mutual labels: imagenet, semantic-segmentation
super-gradientsEasily train or fine-tune SOTA computer vision models with one open source training library
Stars: ✭ 429 (+3200%)
Mutual labels: imagenet, semantic-segmentation
Espnetv2A light-weight, power efficient, and general purpose convolutional neural network
Stars: ✭ 377 (+2800%)
Mutual labels: imagenet, semantic-segmentation
Chainer PspnetPSPNet in Chainer
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Mutual labels: imagenet, semantic-segmentation
ImgclsmobSandbox for training deep learning networks
Stars: ✭ 2,405 (+18400%)
Mutual labels: imagenet, semantic-segmentation
Pytorch Hardnet35% faster than ResNet: Harmonic DenseNet, A low memory traffic network
Stars: ✭ 293 (+2153.85%)
Mutual labels: imagenet, semantic-segmentation
CvatPowerful and efficient Computer Vision Annotation Tool (CVAT)
Stars: ✭ 6,557 (+50338.46%)
Mutual labels: imagenet, semantic-segmentation
SegmentationcppA c++ trainable semantic segmentation library based on libtorch (pytorch c++). Backbone: ResNet, ResNext. Architecture: FPN, U-Net, PAN, LinkNet, PSPNet, DeepLab-V3, DeepLab-V3+ by now.
Stars: ✭ 49 (+276.92%)
Mutual labels: imagenet, semantic-segmentation
Vision4j CollectionCollection of computer vision models, ready to be included in a JVM project
Stars: ✭ 132 (+915.38%)
Mutual labels: imagenet, semantic-segmentation
TorchdistillPyTorch-based modular, configuration-driven framework for knowledge distillation. 🏆18 methods including SOTA are implemented so far. 🎁 Trained models, training logs and configurations are available for ensuring the reproducibiliy.
Stars: ✭ 177 (+1261.54%)
Mutual labels: imagenet, semantic-segmentation
map-floodwater-satellite-imageryThis repository focuses on training semantic segmentation models to predict the presence of floodwater for disaster prevention. Models were trained using SageMaker and Colab.
Stars: ✭ 21 (+61.54%)
Mutual labels: semantic-segmentation
AdaptationSegCurriculum Domain Adaptation for Semantic Segmentation of Urban Scenes, ICCV 2017
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Mutual labels: semantic-segmentation
efficientnetv2.pytorchPyTorch implementation of EfficientNetV2 family
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Mutual labels: imagenet
BottleneckTransformersBottleneck Transformers for Visual Recognition
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Mutual labels: imagenet
SegFormerOfficial PyTorch implementation of SegFormer
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Mutual labels: semantic-segmentation
celldetectionCell Detection with PyTorch.
Stars: ✭ 44 (+238.46%)
Mutual labels: semantic-segmentation
Neural-Machine-TranslationSeveral basic neural machine translation models implemented by PyTorch & TensorFlow
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Mutual labels: pytorch-implmention
