Light-weight neural networks

Vision Transformers are Transformer-like models applied to visual tasks. They stem from the work of ViT which directly applied a Transformer architecture on non-overlapping medium-sized image patches for image classification. Below you can find a continually updating list of vision transformers.

According to [1], ViT type models can be further categorized into uniform scale ViTs, multi-scale ViT, hybrid ViTs with convolutions, and self-supervised ViTs. The methods listed below provide a comprehensive overview of ViT models applied to a range of vision tasks.

[1] Transformers in Vision: A Survey

Semantic Segmentation Models are a class of methods that address the task of semantically segmenting an image into different object classes. Below you can find a continuously updating list of semantic segmentation models.

Object Detection Models are architectures used to perform the task of object detection. Below you can find a continuously updating list of object detection models.

Image Models are methods that build representations of images for downstream tasks such as classification and object detection. The most popular subcategory are convolutional neural networks. Below you can find a continuously updated list of image models.