Generalizing to unseen head poses in facial expression recognition and action unit intensity estimation
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
other normalization methods, FaNC generalizes significantly better than others to unseen poses if they deviate more than 20° from the poses available during training. Code and data are available.
|Title of host publication||The 14th IEEE International Conference on Automatic Face and Gesture Recognition|
|Publication status||Accepted for publication - 22 Jan 2019|
|Event||14th IEEE International Conference on Automatic Face and Gesture Recognition - Lille, France|
Duration: 14 May 2019 → 18 May 2019
|Conference||14th IEEE International Conference on Automatic Face and Gesture Recognition|
|Abbreviated title||FG 2019|
|Period||14/05/19 → 18/05/19|
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Accepted author manuscript (Post-print), 3 MB, PDF-document
Due to publisher’s copyright restrictions, this document is not freely available to download from this website until: 1/01/50