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How Parallel-UNet Transforms Virtual Try-On with Implicit Warping and Unified Operationsby@backpropagation

How Parallel-UNet Transforms Virtual Try-On with Implicit Warping and Unified Operations

by BackpropagationOctober 6th, 2024
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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.
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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.

Abstract and 1. Introduction

2. Related Work

3. Method

3.1. Cascaded Diffusion Models for Try-On

3.2. Parallel-UNet

4. Experiments

5. Summary and Future Work and References


Appendix

A. Implementation Details

B. Additional Results

3.2. Parallel-UNet

The 128×128 Parallel-UNet can be represented as




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].


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 available on arxiv under CC BY-NC-ND 4.0 DEED license.