Semantic Image Synthesis via Class-Adaptive Cross-Attention

Semantic Image Synthesis via Class-Adaptive Cross-Attention

In semantic image synthesis the state of the art is dominated by methods that use customized variants of the SPatially-Adaptive DE-normalization (SPADE) layers, which allow for good visual generation quality and editing versatility. By design, such layers learn pixel-wise modulation parameters to de...

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Bibliographic Details
Main Authors: Tomaso Fontanini, Claudio Ferrari, Giuseppe Lisanti, Massimo Bertozzi, Andrea Prati
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Semantic image synthesis
cross-attention
image editing
Online Access:https://ieeexplore.ieee.org/document/10841835/
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