Forecasting Human Dynamics from Static Images Forecasting Human Dynamics from Static Images
Paper summary Problem ------------- Predict human motion from static image Approach ---------- 1. 2d pose sequence generator 2. convert 2d pose to 3d skeleton 3 Step training strategy ------------------------- 1. Train human 2d pose extractor using annotated video with 2d joint positions 2. 3d skeleton extractor: project mocap data to 2d and use as ground truth for training the 2d->3d skeleton converter 3. Full network training Datasets ----------- 1. Penn Action - Annotated human pose in sports image sequences: bench_press, jumping_jacks, pull_ups... 2. MPII - human action videos with annotated single frame 3. Human3.6M - video, depth and mocap. action include: sitting, purchasing, waiting Evaluation ------------- On the following tasks: 1. 2D pose forecasting 2. 3D pose recovery
Forecasting Human Dynamics from Static Images
Chao, Yu-Wei and Yang, Jimei and Price, Brian L. and Cohen, Scott and Deng, Jia
arXiv e-Print archive - 2017 via Local Bibsonomy
Keywords: dblp

Summary by Kirill Pevzner 3 years ago
Your comment: allows researchers to publish paper summaries that are voted on and ranked!

Sponsored by: and