UMDFaces Dataset

Overview

UMDFaces is a face dataset divided into two parts:
  • Still Images - 367,888 face annotations for 8,277 subjects.
  • Video Frames - Over 3.7 million annotated video frames from over 22,000 videos of 3100 subjects.

Part 1 - Still Images

The dataset contains 367,888 face annotations for 8,277 subjects divided into 3 batches. We provide human curated bounding boxes for faces. We also provide the estimated pose (yaw, pitch, and roll), locations of twenty-one keypoints, and gender information generated by a pre-trained neural network.
In addition, we also release a new face verification test protocol based on batch 3.

Part 2 - Video Frames

The second part contains 3,735,476 annotated video frames extracted from a total of 22,075 for 3,107 subjects. Again, we also provide the estimated pose (yaw, pitch, and roll), locations of twenty-one keypoints, and gender information generated by a pre-trained neural network.

Download

The dataset is temporarily unavailable. We are working to make it available again.

References

If you use our dataset or model, please cite our papers:
  • Ankan Bansal, Anirudh Nanduri, Carlos D Castillo, Rajeev Ranjan, and Rama Chellappa, UMDFaces: An Annotated Face Dataset for Training Deep Networks, Arxiv preprint, 2016.
    Bibtex entry: 
    			@article{bansal2016umdfaces,
			title={UMDFaces: An Annotated Face Dataset for Training Deep Networks},
			author={Bansal, Ankan and Nanduri, Anirudh and Castillo, Carlos D and Ranjan, Rajeev and Chellappa, Rama}
			journal={arXiv preprint arXiv:1611.01484v2},
			year={2016}
			}
  • Ankan Bansal, Carlos Castillo, Rajeev Ranjan, and Rama Chellappa, The Do's and Don'ts for CNN-based Face Verification, Arxiv preprint, 2017.
    Bibtex entry: 
    			@article{bansal2017dosanddonts,
			title = {The Do's and Don'ts for CNN-based Face Verification},
			author = {Bansal, Ankan and Castillo, Carlos and Ranjan, Rajeev and Chellappa, Rama},
			journal = {arXiv preprint arXiv:1705.07426},
			year = {2017}
			}

Change History

  1. May 23rd, 2017: Duplicate subjects removed and new video frame dataset added.
  2. November 21st, 2016: Demo code for fiducial detector added.
  3. November 7th, 2016: New web site.



Last Modified: June 7, 2019. Please direct comments to Ankan Bansal