# Tree-gated Deep Regressor Ensemble For Face Alignment In The Wild

arXiv: https://arxiv.org/abs/1907.03248 · HTML: https://mlsanity.com/paper/1907.03248/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 7 Jul 2019.

## Built on by (most cited first, 1 of 1)

- [Tree-gated Deep Mixture-of-Experts For Pose-robust Face Alignment](https://mlsanity.com/paper/1910.09450/) (2019)

## Abstract (arXiv)

Face alignment consists in aligning a shape model on a face in an image. It is an active domain in computer vision as it is a preprocessing for applications like facial expression recognition, face recognition and tracking, face animation, etc. Current state-of-the-art methods already perform well on "easy" datasets, i.e. those that present moderate variations in head pose, expression, illumination or partial occlusions, but may not be robust to "in-the-wild" data. In this paper, we address this problem by using an ensemble of deep regressors instead of a single large regressor. Furthermore, instead of averaging the outputs of each regressor, we propose an adaptive weighting scheme that uses a tree-structured gate. Experiments on several challenging face datasets demonstrate that our approach outperforms the state-of-the-art methods.