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Xiaolei Huang
Researcher at Penn State College of Information Sciences and Technology
Publications - 187
Citations - 13719
Xiaolei Huang is an academic researcher from Penn State College of Information Sciences and Technology. The author has contributed to research in topics: Image segmentation & Segmentation. The author has an hindex of 39, co-authored 158 publications receiving 11299 citations. Previous affiliations of Xiaolei Huang include Siemens & Princeton University.
Papers
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Proceedings ArticleDOI
Global contrast based salient region detection
TL;DR: This work proposes a regional contrast based saliency extraction algorithm, which simultaneously evaluates global contrast differences and spatial coherence, and consistently outperformed existing saliency detection methods.
Proceedings ArticleDOI
AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks
TL;DR: AttnGAN as mentioned in this paper proposes an attentional generative network to synthesize fine-grained details at different sub-regions of the image by paying attentions to the relevant words in the natural language description.
Journal ArticleDOI
StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks
Han Zhang,Tao Xu,Hongsheng Li,Shaoting Zhang,Xiaogang Wang,Xiaolei Huang,Dimitris N. Metaxas +6 more
TL;DR: Zhang et al. as discussed by the authors proposed a two-stage generative adversarial network architecture, StackGAN-v1, which sketches the primitive shape and colors of a scene based on a given text description, yielding low-resolution images.
Posted Content
StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks
Han Zhang,Tao Xu,Hongsheng Li,Shaoting Zhang,Xiaogang Wang,Xiaolei Huang,Dimitris N. Metaxas +6 more
TL;DR: StackGAN as mentioned in this paper decomposes the text-to-image generation problem into more manageable subproblems through a sketch-refinement process, and introduces a novel Conditioning Augmentation technique that encourages smoothness in the latent conditioning manifold.
Proceedings ArticleDOI
Traffic-Sign Detection and Classification in the Wild
TL;DR: A large traffic-sign benchmark from 100000 Tencent Street View panoramas is created, going beyond previous benchmarks, and it is demonstrated how a robust end-to-end convolutional neural network (CNN) can simultaneously detect and classify trafficsigns.