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We propose a new recurrent generative model for generating images from textcaptions while attending on specific parts of text captions. Our model createsimages by incrementally adding patches on a "canvas" while attending on wordsfrom text caption at each timestep. Finally, the canvas is passed through anupscaling network to generate images. We also introduce a new method forgenerating visual-semantic sentence embeddings based on self-attention overtext. 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 imagegeneration tasks.

CanvasGAN: A simple baseline for text to image generation by incrementally patching a canvas