8 citations · 27 across the 10 of their papers we have counts for
4 papers · 1 filter
DeltaGAN: Towards Diverse Few-shot Image Generation with Sample-Specific Delta
Yan Hong, Li Niu, Jianfu Zhang +2
Learning to generate new images for a novel category based on only a few images, named as few-shot image generation, has attracted increasing research interest. Several state-of-th…
F2GAN: Fusing-and-Filling GAN for Few-shot Image Generation
Yan Hong, Li Niu, Jianfu Zhang +3
In order to generate images for a given category, existing deep generative models generally rely on abundant training images. However, extensive data acquisition is expensive and f…
Beyond without Forgetting: Multi-Task Learning for Classification with Disjoint Datasets
Yan Hong, Li Niu, Jianfu Zhang +1
Multi-task Learning (MTL) for classification with disjoint datasets aims to explore MTL when one task only has one labeled dataset. In existing methods, for each task, the unlabele…
MatchingGAN: Matching-based Few-shot Image Generation
Yan Hong, Li Niu, Jianfu Zhang +1
To generate new images for a given category, most deep generative models require abundant training images from this category, which are often too expensive to acquire. To achieve t…