11 citations · 14 across the 2 of their papers we have counts for
4 papers
Adversarial Learning of Semantic Relevance in Text to Image Synthesis
Miriam Cha, Youngjune L. Gwon, H. T. Kung
We describe a new approach that improves the training of generative adversarial nets (GANs) for synthesizing diverse images from a text input. Our approach is based on the conditio…
Language Modeling by Clustering with Word Embeddings for Text Readability Assessment
Miriam Cha, Youngjune Gwon, H. T. Kung
We present a clustering-based language model using word embeddings for text readability prediction. Presumably, an Euclidean semantic space hypothesis holds true for word embedding…
Adversarial nets with perceptual losses for text-to-image synthesis
Miriam Cha, Youngjune Gwon, H. T. Kung
Recent approaches in generative adversarial networks (GANs) can automatically synthesize realistic images from descriptive text. Despite the overall fair quality, the generated ima…
Multimodal Sparse Coding for Event Detection
Youngjune Gwon, William Campbell, Kevin Brady +3
Unsupervised feature learning methods have proven effective for classification tasks based on a single modality. We present multimodal sparse coding for learning feature representa…