FreeEnricher

KO | EN

gitlite — search

#python #hacktoberfest #react #typescript #go #android #deep-learning #nodejs #macos #java #kubernetes #vue #pytorch #open-source

(★ 19)

FreeEnricher: Enriching Face Landmarks without Additional Cost [Official, AAAI 2023]

FreeEnricher 최신버젼 다운로드

최종 버전 다운로드 (.zip)

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# FreeEnricher: Enriching Face Landmarks without Additional Cost

Paper link: [AAAI 2023](https://arxiv.org/pdf/2212.09525.pdf)

Updated: 12/20/2023

![EnrichedLandmarks](https://raw.githubusercontent.com/huangyangyu/FreeEnricher/main/doc/enriched_landmarks.png)

## Resources

| Dataset          | Dataset                                                            | Metadata (train, test)| Description    |
| :--------------- | :----------------------------------------------------------------- | :-------------------- | -------------- |
| Enriched 300W    | [official](https://ibug.doc.ic.ac.uk/resources/300-W/)             | [google](https://drive.google.com/drive/folders/1X8img5yRyLXV2cBxtbWuCOsNKVQMz1Sm?usp=share_link) / [baidu](https://pan.baidu.com/s/1GOGSpn3PQEYHf23r4eEBHA?pwd=6czg)  | The metadata contains both train.tsv and test.tsv, where train.tsv is refined by FreeEnricher and test.tsv is manually labeled. |
| Enriched WFLW    | [official](https://wywu.github.io/projects/LAB/WFLW.html)          | [google](https://drive.google.com/drive/folders/1egD-fQjfcPoU7daMAQNFxh434Ijz7jLV?usp=share_link) / [baidu](https://pan.baidu.com/s/1NddBa8GIeI8cEADq5XNBSg?pwd=1yme)  | The metadata only contains train.tsv, where train.tsv is refined by FreeEnricher.                                               |

## Structure
| Folder           | Description                                                            |
| :----------------| :--------------------------------------------------------------------- |
| ADNet            | The ADNet codebase of training and testing.                            |
| conf             | The enriched version configure files.                                  |

## Preparation
 - Step1: Clone and Install [ADNet](https://github.com/huangyangyu/ADNet/tree/7f9268449d1605c2f5a00495b93c942f28cd8ac8).
 - Step2: Replace the conf file of [ADNet](https://github.com/huangyangyu/ADNet/tree/7f9268449d1605c2f5a00495b93c942f28cd8ac8) with [enriched version](./conf/alignment.py).
 - Step3: Download dataset and metadata of each dataset to data/alignment/*${dataset}* folder.
 - Step4: Set the target dataset through configuring the *${data_definition}* variable in conf/alignment.py script.
 - Step5: Run the scripts in [ADNet](https://github.com/huangyangyu/ADNet/tree/7f9268449d1605c2f5a00495b93c942f28cd8ac8).

## Framework
The framework of FreeEnricher.
![FreeEnricher](https://raw.githubusercontent.com/huangyangyu/FreeEnricher/main/doc/framework.png)

## Performance
Table 1. Performance of our method on enriched **300W**.

| Method    | Network       | NME<sub>point</sub> | NME<sub>edge</sub> |
| --------- | ------------- | ------------------- | ------------------ |
| Baseline  | ADNet + Line5 | 3.21                | 1.18               |
| **Ours**  | **ADNet-FE5** | **3.06**            | **0.98**           |

Table 2. Comparing with state-of-the-art methods on original **300W** and **WFLW**.

| Method        | 300W           | WFLW           |
| ------------- | -------------- | -------------- |
| LAB           | 3.49           | 5.27           |
| HRNet         | 3.34           | 4.60           |
| LUVLi         | 3.23           | 4.37           |
| ADNet         | 2.93           | 4.14           |
| **ADNet-FE5** | **2.87**       | **4.10**       |

## Citation

```
@inproceedings{huang2023freeenricher,
  title={FreeEnricher: enriching face landmarks without additional cost},
  author={Huang, Yangyu and Chen, Xi and Kim, Jongyoo and Yang, Hao and Li, Chong and Yang, Jiaolong and Chen, Dong},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={37},
  number={1},
  pages={962--970},
  year={2023}
}
```

## License

The project is released under the MIT License

FreeEnricher

FreeEnricher 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

FreeEnricher

FreeEnricher 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

Download README