English

Visualizing the decision-making process in deep neural decision forest

Computer Vision and Pattern Recognition 2019-04-22 v1 Artificial Intelligence

Abstract

Deep neural decision forest (NDF) achieved remarkable performance on various vision tasks via combining decision tree and deep representation learning. In this work, we first trace the decision-making process of this model and visualize saliency maps to understand which portion of the input influence it more for both classification and regression problems. We then apply NDF on a multi-task coordinate regression problem and demonstrate the distribution of routing probabilities, which is vital for interpreting NDF yet not shown for regression problems. The pre-trained model and code for visualization will be available at https://github.com/Nicholasli1995/VisualizingNDF

Keywords

Cite

@article{arxiv.1904.09201,
  title  = {Visualizing the decision-making process in deep neural decision forest},
  author = {Shichao Li and Kwang-Ting Cheng},
  journal= {arXiv preprint arXiv:1904.09201},
  year   = {2019}
}

Comments

Accepted by CVPR 2019 workshops on explainable AI

R2 v1 2026-06-23T08:44:46.553Z