71 citations · 416 across the 50 of their papers we have counts for
6 papers · 1 filter
Learning Transformations for Classification Forests
Qiang Qiu, Guillermo Sapiro
This work introduces a transformation-based learner model for classification forests. The weak learner at each split node plays a crucial role in a classification tree. We propose…
Learning Transformations for Clustering and Classification
Qiang Qiu, Guillermo Sapiro
A low-rank transformation learning framework for subspace clustering and classification is here proposed. Many high-dimensional data, such as face images and motion sequences, appr…
Sparse Dictionary-based Attributes for Action Recognition and Summarization
Qiang Qiu, Zhuolin Jiang, Rama Chellappa
We present an approach for dictionary learning of action attributes via information maximization. We unify the class distribution and appearance information into an objective funct…
Domain-invariant Face Recognition using Learned Low-rank Transformation
Qiang Qiu, Guillermo Sapiro, Ching-Hui Chen
We present a low-rank transformation approach to compensate for face variations due to changes in visual domains, such as pose and illumination. The key idea is to learn discrimina…
Learning Robust Subspace Clustering
Qiang Qiu, Guillermo Sapiro
We propose a low-rank transformation-learning framework to robustify subspace clustering. Many high-dimensional data, such as face images and motion sequences, lie in a union of lo…
Compositional Dictionaries for Domain Adaptive Face Recognition
Qiang Qiu, Rama Chellappa
We present a dictionary learning approach to compensate for the transformation of faces due to changes in view point, illumination, resolution, etc. The key idea of our approach is…