# ADE20k Fine-tuning

A general-purpose image segmentation model trained on the ADE20k dataset, using a unified framework to handle instance/semantic/panoptic segmentation tasks

Mask2Former model trained on the ADE20k panoptic segmentation dataset using a Swin large backbone network, employing a unified paradigm to handle instance segmentation, semantic segmentation, and panoptic segmentation tasks.

BEiT is a model based on the Vision Transformer (ViT) architecture, pre-trained on ImageNet-21k through self-supervised learning and fine-tuned on the ADE20k dataset, specifically designed for image semantic segmentation tasks.