3,403 research outputs found
CanvasGAN: A simple baseline for text to image generation by incrementally patching a canvas
We propose a new recurrent generative model for generating images from text
captions while attending on specific parts of text captions. Our model creates
images by incrementally adding patches on a "canvas" while attending on words
from text caption at each timestep. Finally, the canvas is passed through an
upscaling network to generate images. We also introduce a new method for
generating visual-semantic sentence embeddings based on self-attention over
text. We compare our model's generated images with those generated Reed et.
al.'s model and show that our model is a stronger baseline for text to image
generation tasks.Comment: CVC 201
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