AttLWB
Attentional Liquid Warping Block
**Attentional Liquid Warping Block**, or **AttLWB**, is a module for human image synthesis GANs that propagates the source information - such as texture, style, color and face identity - in both image and feature spaces to the synthesized reference. It firstly learns similarities of the global features among all multiple sources features, and then it fuses the multiple sources features by a linear combination of the learned similarities and the multiple sources in the feature spaces. Finally, to better propagate the source identity (style, color, and texture) into the global stream, the fused source features are warped to the global stream by [Spatially-Adaptive Normalization](https://paperswithcode.com/method/spade) (SPADE).
Liquid Warping GAN with Attention: A Unified Framework for Human Image Synthesis
https://paperswithcode.com/paper/liquid-warping-gan-with-attention-a-unified
Liquid Warping GAN with Attention: A Unified Framework for Human Image Synthesis