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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
High-quality Neural Networks for Computer Vision 😎
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| 2026-07-24 | 447 |
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| 2026-08-06 | 447 |
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# Glasses 😎  [](https://codecov.io/gh/FrancescoSaverioZuppichini/glasses) Compact, concise and customizable deep learning computer vision library **Models have been stored into the [hugging face hub!](https://huggingface.co/glasses)** Doc is [here](https://francescosaveriozuppichini.github.io/glasses/index.html) ## TL;DR This library has - human readable code, no *research code* - common component are shared across [models](#Models) - [same APIs](#classification) for all models (you learn them once and they are always the same) - clear and easy to use model constomization (see [here](#block)) - [classification](#classification) and [segmentation](#segmentation) - emoji in the name ;) Stuff implemented so far: - [Training data-efficient image transformers & distillation through attention](https://arxiv.org/pdf/2012.12877.pdf) - [Vision Transformer - An Image Is Worth 16x16 Words: Transformers For Image Recognition At Scale](https://arxiv.org/pdf/2010.11929.pdf) - [ResNeSt: Split-Attention Networks](https://arxiv.org/abs/2004.08955) - [AlexNet- ImageNet Classification with Deep Convolutional Neural Networks](https://papers.nips.cc/paper/2012/file/c399862d3b9d6b76c8436e924a68c45b-Paper.pdf) - [DenseNet - Densely Connected Convolutional Networks](https://arxiv.org/abs/1608.06993) - [EfficientNet - EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks](https://arxiv.org/abs/1905.11946) - [EfficientNetLite - Higher accuracy on vision models with EfficientNet-Lite](https://blog.tensorflow.org/2020/03/higher-accuracy-on-vision-models-with-efficientnet-lite.html) - [FishNet - FishNet: A Versatile Backbone for Image, Region, and Pixel Level Prediction ](https://arxiv.org/abs/1901.03495) - [MobileNet - MobileNetV2: Inverted Residuals and Linear Bottlenecks](https://arxiv.org/pdf/1801.04381.pdf) - [RegNet - Designing Network Design Spaces](https://arxiv.org/abs/2003.13678) - [ResNet - Deep Residual Learning for Image Recognition](https://arxiv.org/abs/1512.03385) - [ResNetD - Bag of Tricks for Image Classification with Convolutional Neural Networks](https://arxiv.org/pdf/1812.01187.pdf) - [ResNetXt - Aggregated Residual Transformations for Deep Neural Networks](https://arxiv.org/pdf/1611.05431.pdf) - [SEResNet - Concurrent Spatial and Channel Squeeze & Excitation in Fully Convolutional Networks](https://arxiv.org/abs/1803.02579) - [VGG - Very Deep Convolutional Networks For Large-scale Image Recognition](https://arxiv.org/pdf/1409.1556.pdf) - [WideResNet - Wide Residual Networks](https://arxiv.org/pdf/1605.07146.pdf) - [FPN - Feature Pyramid Networks for Object Detection](https://arxiv.org/abs/1612.03144) - [PFPN - Panoptic Feature Pyramid Networks](https://arxiv.org/pdf/1901.02446.pdf) - [UNet - U-Net: Convolutional Networks for Biomedical Image Segmentation](https://arxiv.org/abs/1505.04597) - [Squeeze and Excitation - Concurrent Spatial and Channel Squeeze & Excitation in Fully Convolutional Networks](https://arxiv.org/abs/1803.02579) - [ECA - ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks](https://arxiv.org/pdf/1910.03151.pdf) - [DropBlock: A regularization method for convolutional networks](https://arxiv.org/abs/1810.12890) - [Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition](https://arxiv.org/pdf/1406.4729.pdf) - [Score-CAM: Score-Weighted Visual Explanations for Convolutional Neural Networks](https://arxiv.org/abs/1910.01279) - [Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization](https://arxiv.org/abs/1610.02391) ## Installation You can install `glasses` using pip by running ``` pip install git+https://github.com/FrancescoSaverioZuppichini/glasses ``` ### Motivations Almost all existing implem
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:c4f6b09b968d775a, topic:deep-learning, topic:neural-network, topic:pytorch
matched fp:c4f6b09b968d775a, topic:computer-vision, desc:computer vision, readme:computer vision