431 citations · 914 across the 7 of their papers we have counts for
7 papers
Toward Characteristic-Preserving Image-based Virtual Try-On Network
Bochao Wang, Huabin Zheng, Xiaodan Liang +3
Image-based virtual try-on systems for fitting new in-shop clothes into a person image have attracted increasing research attention, yet is still challenging. A desirable pipeline…
Large-Margin Softmax Loss for Convolutional Neural Networks
Weiyang Liu, Yandong Wen, Zhiding Yu +1
Cross-entropy loss together with softmax is arguably one of the most common used supervision components in convolutional neural networks (CNNs). Despite its simplicity, popularity…
Robust Elastic Net Regression
Weiyang Liu, Rongmei Lin, Meng Yang
We propose a robust elastic net (REN) model for high-dimensional sparse regression and give its performance guarantees (both the statistical error bound and the optimization bound)…
Jointly Learning Non-negative Projection and Dictionary with Discriminative Graph Constraints for Classification
Weiyang Liu, Zhiding Yu, Yandong Wen +2
Sparse coding with dictionary learning (DL) has shown excellent classification performance. Despite the considerable number of existing works, how to obtain features on top of whic…
Structured Occlusion Coding for Robust Face Recognition
Yandong Wen, Weiyang Liu, Meng Yang +3
Occlusion in face recognition is a common yet challenging problem. While sparse representation based classification (SRC) has been shown promising performance in laboratory conditi…
Collaborative Representation based Classification for Face Recognition
Lei Zhang, Meng Yang, Xiangchu Feng +2
By coding a query sample as a sparse linear combination of all training samples and then classifying it by evaluating which class leads to the minimal coding residual, sparse repre…
Regularized Robust Coding for Face Recognition
Meng Yang, Lei Zhang, Jian Yang +1
Recently the sparse representation based classification (SRC) has been proposed for robust face recognition (FR). In SRC, the testing image is coded as a sparse linear combination…