most citedNITES: A Non-Parametric Interpretable Texture Synthesis Method

10 citations · 35 across the 6 of their papers we have counts for

collaborators

7 papers

cs.LG20209 cited

From Two-Class Linear Discriminant Analysis to Interpretable Multilayer Perceptron Design

Ruiyuan Lin, Zhiruo Zhou, Suya You +2

A closed-form solution exists in two-class linear discriminant analysis (LDA), which discriminates two Gaussian-distributed classes in a multi-dimensional feature space. In this wo…

cs.CV202010 cited

NITES: A Non-Parametric Interpretable Texture Synthesis Method

Xuejing Lei, Ganning Zhao, C. -C. Jay Kuo

A non-parametric interpretable texture synthesis method, called the NITES method, is proposed in this work. Although automatic synthesis of visually pleasant texture can be achieve…

cs.CV2020

Unsupervised Point Cloud Registration via Salient Points Analysis (SPA)

Pranav Kadam, Min Zhang, Shan Liu +1

An unsupervised point cloud registration method, called salient points analysis (SPA), is proposed in this work. The proposed SPA method can register two point clouds effectively u…

cs.CV20201 cited

Unsupervised Feedforward Feature (UFF) Learning for Point Cloud Classification and Segmentation

Min Zhang, Pranav Kadam, Shan Liu +1

In contrast to supervised backpropagation-based feature learning in deep neural networks (DNNs), an unsupervised feedforward feature (UFF) learning scheme for joint classification…

cs.CV20208 cited

Learning Color Compatibility in Fashion Outfits

Heming Zhang, Xuewen Yang, Jianchao Tan +3

Color compatibility is important for evaluating the compatibility of a fashion outfit, yet it was neglected in previous studies. We bring this important problem to researchers' att…

cs.CV20205 cited

Novel Human-Object Interaction Detection via Adversarial Domain Generalization

Yuhang Song, Wenbo Li, Lei Zhang +6

We study in this paper the problem of novel human-object interaction (HOI) detection, aiming at improving the generalization ability of the model to unseen scenarios. The challenge…