![Table 1. Quantitative comparison to 3 baselines. We compute FID and KID on our 6K test set and VITON-HD’s unpaired test set. The KID is scaled by 1000 following [22].](http://hackernoon.imgix.net/images/fWZa4tUiBGemnqQfBGgCPf9594N2-j6b303c.png?auto=format&fit=max&w=1080)
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How Parallel-UNet Transforms Virtual Try-On with Implicit Warping and Unified Operations by@backpropagation
How Parallel-UNet Transforms Virtual Try-On with Implicit Warping and Unified Operations
by BackpropagationOctober 6th, 2024
Too Long; Didn't Read
The 128×128 Parallel-UNet employs implicit warping using a cross attention mechanism to manage complex transformations like garment warping. By combining warping and blending into a single pass, the architecture utilizes two UNets to efficiently process person and garment images. Pose embeddings guide these operations, enhancing the correspondence between the target person and the garment.Authors:
(1) Luyang Zhu, University of Washington and Google Research, and work done while the author was an intern at Google; (2) Dawei Yang, Google Research; (3) Tyler Zhu, Google Research; (4) Fitsum Reda, Google Research; (5) William Chan, Google Research; (6) Chitwan Saharia, Google Research; (7) Mohammad Norouzi, Google Research; (8) Ira Kemelmacher-Shlizerman, University of Washington and Google Research.Table of Links
3.1. Cascaded Diffusion Models for Try-On
5. Summary and Future Work and References
Appendix
3.2. Parallel-UNet
The 128×128 Parallel-UNet can be represented as
Combining warp and blend in a single pass. Instead of warping the garment to the target body and then blending with the target person as done by prior works, we combine the two operations into a single pass. As shown in Fig. 2, we achieve it via two UNets that handle the garment and the person respectively.
This paper is under CC BY-NC-ND 4.0 DEED license.
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