Large-scale CelebFaces Attributes (CelebA) Dataset


  
    
      
      
	Large-scale CelebFaces Attributes (CelebA) Dataset


	

	
	
	  Ziwei Liu  
	  Ping Luo  
	  Xiaogang Wang  
	  Xiaoou Tang
	


	
	  Multimedia Laboratory, 
	  
	  The Chinese University of Hong Kong
	


      


      
      
	  
	  
	  
	  
	News

	
	2020-07-10 Two related datasets, CelebAMask-HQ and CelebA-Spoof, have been released.  


	2016-07-29 If Dropbox is not accessible, please download the dataset using Google Drive or Baidu Drive (password: rp0s).


     



	Details

    
	


	CelebFaces Attributes Dataset (CelebA) is a large-scale face attributes dataset with more than 200K celebrity images, each with 40 attribute annotations. The images in this dataset cover large pose variations and background clutter. CelebA has large diversities, large quantities, and rich annotations, including


		10,177 number of identities,

	
	202,599 number of face images, and

	
	5 landmark locations, 40 binary attributes annotations per image.

	


	The dataset can be employed as the training and test sets for the following computer vision tasks: face attribute recognition, face detection, landmark (or facial part) localization, and face editing & synthesis. 

    






	Sample Images

	

	
	

      






	Downloads


	  	
	      
		

		  In-The-Wild Images
		

	      
	
	      
		

		  Align&Cropped Images
		

	      
	
	      
		

		  Landmarks Annotations
		

	      
	
	      
		

		  Attributes Annotations
		

	      
	
	      
		

		  Identities Annotations
		

	      


	    
	    

	    




	Evaluation


	  	
	      
		

		  Train/Val/Test Partitions
		

	      


	    
	    

	    

		
		If the above links are not accessable, you could download the dataset using Baidu Drive.


	    For more details of the dataset, please refer to the paper "Deep Learning Face Attributes in the Wild".

	    

	    




	Agreement

		The CelebA dataset is available for non-commercial research purposes only.
	All images of the CelebA dataset are obtained from the Internet which are not property of MMLAB, The Chinese University of Hong Kong. The MMLAB is not responsible for the content nor the meaning of these images.
	You agree not to reproduce, duplicate, copy, sell, trade, resell or exploit for any commercial purposes, any portion of the images and any portion of derived data.
	You agree not to further copy, publish or distribute any portion of the CelebA dataset. Except, for internal use at a single site within the same organization it is allowed to make copies of the dataset.
	The MMLAB reserves the right to terminate your access to the CelebA dataset at any time.
	The face identities are released upon request for research purposes only. Please contact us for details.


    

	
	
	Citation

	
	  @inproceedings{liu2015faceattributes,
 title = {Deep Learning Face Attributes in the Wild},
 author = {Liu, Ziwei and Luo, Ping and Wang, Xiaogang and Tang, Xiaoou},
 booktitle = {Proceedings of International Conference on Computer Vision (ICCV)},
 month = {December},
 year = {2015} 
}

	  
	

   	

	
	
	
	Related Datasets


	  	
	      
		

		  LFWA+ Dataset
		

	      
	
	      
		

		  CelebAMask-HQ Dataset
		

	      
	
	      
		

		  CelebA-Spoof Dataset
		

	      



	    




	

	Contact

	
	


	Please contact Ping Luo and Ziwei Liu for questions about the dataset.