DC Field | Value | Language |
---|---|---|
dc.contributor.author | Yoo, Sahng-Min | ko |
dc.contributor.author | Choi, Tae-Min | ko |
dc.contributor.author | Choi, Jae-Woo | ko |
dc.contributor.author | Kim, Jong-Hwan | ko |
dc.date.accessioned | 2023-04-05T06:05:28Z | - |
dc.date.available | 2023-04-05T06:05:28Z | - |
dc.date.created | 2023-03-31 | - |
dc.date.issued | 2023-01 | - |
dc.identifier.citation | 23rd IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2023, pp.3547 - 3556 | - |
dc.identifier.uri | http://hdl.handle.net/10203/305997 | - |
dc.description.abstract | Recent face swapping frameworks have achieved high-fidelity results. However, the previous works suffer from high computation costs due to the deep structure and the use of off-the-shelf networks. To overcome such problems and achieve real-time face swapping, we propose a lightweight one-stage framework, FastSwap. We design a shallow network trained in a self-supervised manner without any manual annotations. The core of our framework is a novel decoder block, called Triple Adaptive Normalization (TAN) block, which effectively integrates the identity and pose information. Besides, we propose a novel data augmentation and switch-test strategy to extract the attributes from the target image, which further enables controllable attribute editing. Extensive experiments on VoxCeleb2 and wild faces demonstrate that our framework generates high-fidelity face swapping results in 123.22 FPS and better preserves the identity, pose, and attributes than other state-of-the-art methods. Furthermore, we conduct an in-depth study to demonstrate the effectiveness of our proposal. | - |
dc.language | English | - |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
dc.title | FastSwap: A Lightweight One-Stage Framework for Real-Time Face Swapping | - |
dc.type | Conference | - |
dc.identifier.scopusid | 2-s2.0-85149047196 | - |
dc.type.rims | CONF | - |
dc.citation.beginningpage | 3547 | - |
dc.citation.endingpage | 3556 | - |
dc.citation.publicationname | 23rd IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2023 | - |
dc.identifier.conferencecountry | US | - |
dc.identifier.conferencelocation | Waikoloa, HI | - |
dc.identifier.doi | 10.1109/WACV56688.2023.00355 | - |
dc.contributor.localauthor | Kim, Jong-Hwan | - |
dc.contributor.nonIdAuthor | Yoo, Sahng-Min | - |
dc.contributor.nonIdAuthor | Choi, Tae-Min | - |
dc.contributor.nonIdAuthor | Choi, Jae-Woo | - |
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