1 citations · 2 across the 4 of their papers we have counts for
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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…
Two-Stream FCNs to Balance Content and Style for Style Transfer
Duc Minh Vo, Akihiro Sugimoto
Style transfer is to render given image contents in given styles, and it has an important role in both computer vision fundamental research and industrial applications. Following t…
Visual-Relation Conscious Image Generation from Structured-Text
Duc Minh Vo, Akihiro Sugimoto
We propose an end-to-end network for image generation from given structured-text that consists of the visual-relation layout module and the pyramid of GANs, namely stacking-GANs. O…