metadata

dataset_info:
  - config_name: multisigner
    features:
      - name: tokens
        sequence: string
      - name: frames
        sequence: image
    splits:
      - name: train
        num_bytes: 35090699166
        num_examples: 5672
      - name: validation
        num_bytes: 3294861848
        num_examples: 540
      - name: test
        num_bytes: 3935889563
        num_examples: 629
    download_size: 43042303939
    dataset_size: 42321450577
  - config_name: signerindependent
    features:
      - name: tokens
        sequence: string
      - name: frames
        sequence: image
    splits:
      - name: train
        num_bytes: 26933878872
        num_examples: 4376
      - name: validation
        num_bytes: 720567494
        num_examples: 111
      - name: test
        num_bytes: 1175795394
        num_examples: 180
    download_size: 29320607031
    dataset_size: 28830241760

RWTH-Weather-Phoenix 2014

This archive contains two sets of the RWTH-Weather-Phoenix 2014 corpus

the multisigner set
the signer independent set.

It is released under non-commercial cc 4.0 license with attribution (see attachment)

If you use this data in your research, please cite:

O. Koller, J. Forster, and H. Ney. Continuous sign language recognition: Towards large vocabulary statistical recognition systems handling multiple signers. Computer Vision and Image Understanding, volume 141, pages 108-125, December 2015.

and

Koller, Zargaran, Ney. "Re-Sign: Re-Aligned End-to-End Sequence Modeling with Deep Recurrent CNN-HMMs" in CVPR 2017, Honululu, Hawaii, USA.

See README files in subfolders for more information.

CHANGELOG

v1 Aug 20 2016, initial version of the archive. multisigner setup
v2 Apr 21 2017, signer independent SI5 subset, added caffe models and automatic frame-alignment
v3 Nov 3 2017, added language models and complete set of hyper parameters to reproduce the published results