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:fire: [ICLR2023, ECCV2022, TPAMI2024] Powerful Multi-Task Transformers for Scene Understanding

:scroll: Introduction

This repository provides codes and models for two powerful multi-task transformer models for scene understanding. Please check the following pages for details:

Hanrong Ye and Dan Xu, TaskPrompter: Spatial-Channel Multi-Task Prompting for Dense Scene Understanding. ICLR 2023

<p align="center"> <img alt="img-name" src="https://user-images.githubusercontent.com/14089338/232197965-8936504d-8ce4-450b-a281-069f5c2c8205.gif" width="900"> </p>

Hanrong Ye and Dan Xu, Inverted Pyramid Multi-task Transformer for Dense Scene Understanding. ECCV 2022

<p align="center"> <img alt="img-name" src="https://user-images.githubusercontent.com/14089338/220043972-b3bfcc0d-d76e-4d34-8b20-d7c5d9f00a9f.gif" width="900"> <img alt="img-name" src="https://user-images.githubusercontent.com/14089338/220043986-291797a8-8994-4a54-846e-057e3778a972.gif" width="900"> </p>

Cite

BibTex:

@InProceedings{invpt2022,
  title={Inverted Pyramid Multi-task Transformer for Dense Scene Understanding},
  author={Ye, Hanrong and Xu, Dan},
  booktitle={ECCV},
  year={2022}
}
@InProceedings{taskprompter2023,
  title={TaskPrompter: Spatial-Channel Multi-Task Prompting for Dense Scene Understanding},
  author={Ye, Hanrong and Xu, Dan},
  booktitle={ICLR},
  year={2023}
}
@article{ye2023invpt++,
  title={InvPT++: Inverted Pyramid Multi-Task Transformer for Visual Scene Understanding},
  author={Ye, Hanrong and Xu, Dan},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2024}
}

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Contact

Please contact Hanrong Ye if any questions.

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Few-show learning of multiple tasks: Visual Token Matching (ICLR 2023 Outstanding Paper Award)