How2Sign consists of a parallel corpus of 80 hours of sign language videos (collected with multi-view RGB and depth sensor data) with corresponding speech transcriptions and gloss annotations. In addition, a three-hour subset was further recorded in a geodesic dome setup using hundreds of cameras and sensors, which enables detailed 3D reconstruction and pose estimation and paves the way for vision systems to understand the 3D geometry of sign language.
Videos selected from the existing How2 dataset
Ramon Sanabria, Ozan Caglayan, Shruti Palaskar, Desmond
Elliott, Lo¨ıc Barrault, Lucia Specia, and Florian Metze.
How2: a large-scale dataset for multimodal language understanding. arXiv preprint arXiv:1811.00347, 2018
https://github.com/srvk/how2-dataset
Script download the files directly to their servers (preferably via wget) https://github.com/how2sign/how2sign.github.io/blob/main/download_how2sign.sh