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Found 4 papers, 1 papers with code
Domain Disentangled Generative Adversarial Network for Zero-Shot Sketch-Based 3D Shape Retrieval
Then, we develop a generative adversarial network that combines the domain-specific features of the seen categories with the aligned domain-invariant features to synthesize samples, where the synthesized samples of the unseen categories are generated by using the corresponding word embeddings.
Contrastive Embedding for Generalized Zero-Shot Learning
To tackle this issue, we propose to integrate the generation model with the embedding model, yielding a hybrid GZSL framework.
Learning the Redundancy-free Features for Generalized Zero-Shot Object Recognition
Zero-shot object recognition or zero-shot learning aims to transfer the object recognition ability among the semantically related categories, such as fine-grained animal or bird species.
AIM 2019 Challenge on Image Demoireing: Methods and Results
A new dataset, called LCDMoire was created for this challenge, and consists of 10, 200 synthetically generated image pairs (moire and clean ground truth).
