BachGAN: High-Res Image Synthesis from Salient Object Layout
We propose a new task towards more practical application for image generation - high-quality image synthesis from salient object layout.
generative-adversarial-networks salient-object-layout image-generation image-synthesis pytorch computer-vision research
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Objectives & Highlights

Two main challenges spring from this new task: • (i) how to generate fine-grained details and realistic textures without segmentation map input; and • (ii) how to create a background and weave it seamlessly into standalone objects. To tackle this, we propose Background Hallucination Generative Adversarial Network (BachGAN), which first selects a set of segmentation maps from a large candidate pool via a background retrieval module, then encodes these candidate layouts via a background fusion module to hallucinate a suitable background for the given objects.

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Ph.D. Student in CRCV of UCF.
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