EDFace-Celeb-1M: Benchmarking Face Hallucination with a Million-scale Dataset (TPAMI2022)

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License

The EDFace-Celeb dataset is released under CC BY-NC-ND license.

Our propsoed EDFace-Celeb-1M Dataset

We construct a large-scale dataset for face analysis. It consists of three sub-datasets, i.e., EDFace-Celeb-1M, EDFace-Celeb-150K and EDFace-Celeb-Real datasets. The EDFace-Celeb-1M and EDFace-Celeb-150K datasets provide different settings for face super-resolution (FH128, FH512), face hallucination (FH128, FH512) and blind face restoration (BFR128, BFR512).

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EDFace-Celeb-Real: Real-world low-resolution face images.

Download

• Google Drive (Unavailable)
• Baidu Cloud

EDFace-Celeb-1M (FH128): Face Hallucination (HR, LR: X2, X4, X4_BD, X4_DN, X8)

Download

• Google Drive (Unavailable)
• Baidu Cloud

Citation:

• EDFace-Celeb-1M: Benchmarking Face Hallucination with a Million-scale Dataset (TPAMI2022)

Benchmarking Results (X2, X4, X4_BD, X4_DN, X8)

• DIC: Results
• DIC-GAN: Results
• HiFaceGAN: Results
• Wavelet: Results
• EDSR: Results
• RCAN: Results
• RDN: Results
• HAN: Results

EDFace-Celeb-150K (FH512) : Face Hallucination (HR, LR: X2, X4, X4_BD, X4_DN, X8)

Download

• Google Drive (Unavailable)
• Baidu Cloud

Citation:

• EDFace-Celeb-1M: Benchmarking Face Hallucination with a Million-scale Dataset (TPAMI2022)

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EDFace-Celeb-1M (BFR128) : Blind Face Restoration (HQ, LQ: Blur, JPEG artifact, Noise, SR, Full, Full_X2, Full_X4, Full_X8)

Download

• Google Drive (Unavailable)
• Baidu Cloud

Citation:

• EDFace-Celeb-1M: Benchmarking Face Hallucination with a Million-scale Dataset (TPAMI2022)
• Blind Face Restoration: Benchmark Datasets and a Baseline Model

EDFace-Celeb-150K (BFR512): Blind Face Restoration (HQ, LQ: Blur, JPEG artifact, Noise, SR, Full, Full_X2, Full_X4, Full_X8)

Download

• Google Drive (Unavailable)
• Baidu Cloud

Citation:

• EDFace-Celeb-1M: Benchmarking Face Hallucination with a Million-scale Dataset (TPAMI2022)
• Blind Face Restoration: Benchmark Datasets and a Baseline Model

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Citation

If you think the EDFace-Celeb dataset is useful for your research, please cite the following paper.

@inproceedings{zhang2022edface,
  title={EDFace-Celeb-1M: Benchmarking Face Hallucination with a Million-scale Dataset},
  author={Zhang, Kaihao and Li, Dongxu and Luo, Wenhan and Liu, Jingyu and Deng, Jiankang and Liu, Wei and Stefanos Zafeiriou},
  booktitle={IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},
  year={2022}
}