Research focusing on multimodal models and longitudinal study designs.
Authors: Amanda Duarte, et al. Venue: CVPR 2021 BFH03_03.mp4
This paper introduces the dataset containing over 80 hours of instructional videos, including the BFH (Body-Face-Hands) keypoint annotations mentioned in your file name. You can access more information via the How2Sign Project Page . Dataset Context You can access more information via the How2Sign
The naming convention "BFH" typically refers to keypoints, which are high-resolution 2D or 3D skeletal data extracted from RGB videos. In the How2Sign dataset: How2Sign Dataset Other related research, such as the
Specialized methods using Multi-Channel MKL for detecting characteristics in video sequences. How2Sign Dataset
Other related research, such as the , also uses a BFH subset for evaluating the accuracy of 3D human meshes.
The video file is a specific clip from the How2Sign dataset , a large-scale multimodal collection of American Sign Language (ASL) videos designed for computer vision research. Primary Research Paper