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High Resolution and Fast Face Completion via Progressively Attentive GANs
Face completion is a challenging task with the difficulty level increasing significantly with respect to high resolution, the complexity of "holes" and the controllable attributes of filled-in fragments.
Abstractive Summarization of Large Document Collections Using GPT
This paper proposes a method of abstractive summarization designed to scale to document collections instead of individual documents.
Towards Controllable and Interpretable Face Completion via Structure-Aware and Frequency-Oriented Attentive GANs
The proposed frequency-oriented attentive module (FOAM) encourages GANs to attend to only finer details in the coarse-to-fine progressive training, thus enabling progressive attention to face structures.
High Resolution Face Completion with Multiple Controllable Attributes via Fully End-to-End Progressive Generative Adversarial Networks
It is a challenging task with the difficulty level increasing significantly with respect to high resolution, the complexity of "holes" and the controllable attributes of filled-in fragments.
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