29 citations · 63 across the 19 of their papers we have counts for
30 papers
Character-Centric Story Visualization via Visual Planning and Token Alignment
Hong Chen, Rujun Han, Te-Lin Wu +2
Story visualization advances the traditional text-to-image generation by enabling multiple image generation based on a complete story. This task requires machines to 1) understand…
StoryER: Automatic Story Evaluation via Ranking, Rating and Reasoning
Hong Chen, Duc Minh Vo, Hiroya Takamura +2
Existing automatic story evaluation methods place a premium on story lexical level coherence, deviating from human preference. We go beyond this limitation by considering a novel \…
OSSGAN: Open-Set Semi-Supervised Image Generation
Kai Katsumata, Duc Minh Vo, Hideki Nakayama
We introduce a challenging training scheme of conditional GANs, called open-set semi-supervised image generation, where the training dataset consists of two parts: (i) labeled data…
NOC-REK: Novel Object Captioning with Retrieved Vocabulary from External Knowledge
Duc Minh Vo, Hong Chen, Akihiro Sugimoto +1
Novel object captioning aims at describing objects absent from training data, with the key ingredient being the provision of object vocabulary to the model. Although existing metho…
PPCD-GAN: Progressive Pruning and Class-Aware Distillation for Large-Scale Conditional GANs Compression
Duc Minh Vo, Akihiro Sugimoto, Hideki Nakayama
We push forward neural network compression research by exploiting a novel challenging task of large-scale conditional generative adversarial networks (GANs) compression. To this en…
SciXGen: A Scientific Paper Dataset for Context-Aware Text Generation
Hong Chen, Hiroya Takamura, Hideki Nakayama
Generating texts in scientific papers requires not only capturing the content contained within the given input but also frequently acquiring the external information called \textit…