https://github.com/jin-s13/unifs

https://github.com/jin-s13/unifs

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• Host: GitHub
• URL: https://github.com/jin-s13/unifs
• Owner: jin-s13
• Created: 2024-07-08T03:09:55.000Z (4 months ago)
• Default Branch: main
• Last Pushed: 2024-07-14T08:30:28.000Z (4 months ago)
• Last Synced: 2024-07-14T17:47:31.577Z (4 months ago)
• Size: 309 KB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# UniFS

## Introduction

This repo contains the official PyTorch implementation of our ECCV'2024 paper

[UniFS: Universal Few-shot Instance Perception with Point Representations](https://arxiv.org/abs/2404.19401).



## Data Preparation

We evaluate our models on  [COCO-UniFS](https://drive.google.com/file/d/1H878NXuehoynWWfI6CloD0yNBKtbQzko/view?usp=sharing)

benchmark. This benchmark is built upon several existing datasets, including [MSCOCO](https://cocodataset.org/#download) and [MISC](https://github.com/YXSUNMADMAX/MISC210K).

The [COCO-UniFS](https://drive.google.com/file/d/1H878NXuehoynWWfI6CloD0yNBKtbQzko/view?usp=sharing) benchmark provides dense annotations for four fundamental few-shot computer vision tasks: object detection, 

instance segmentation, pose estimation, and object counting. The annotations for object detection and 

instance segmentation are directly taken from the MSCOCO dataset, which

provides bounding box and per-instance segmentation mask annotations for 80

object categories. For pose estimation, we extend the MSCOCO dataset by

adding instance-level keypoint annotations for 34 object categories from the

MISC dataset. The MISC dataset was originally designed for multi-instance

semantic correspondence, and we adapted it to fit the few-shot pose estimation

task.

The dataset split follows [DeFRCN](https://github.com/er-muyue/DeFRCN). 

  - Unzip the downloaded [COCO-UniFS](https://drive.google.com/file/d/1H878NXuehoynWWfI6CloD0yNBKtbQzko/view?usp=sharing) data-source to `datasets` and put it into your project directory:

    ```angular2html

      ...

      datasets

        | -- coco (trainval2014/*.jpg, val2014/*.jpg, annotations/*.json)

        | -- unifs_cocosplit

      unifS

      tools

      ...

    ```

## Acknowledgement

This repo is developed based on [DCFS](https://github.com/gaobb/DCFS), [DeFRCN](https://github.com/er-muyue/DeFRCN) and [Detectron2](https://github.com/facebookresearch/detectron2). 

## License

UniFS is freely available for free non-commercial use, and may be redistributed under these conditions. For commercial queries, please contact Mr. Sheng Jin (jinsheng13[at]foxmail[dot]com). We will send the detail agreement to you.