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ArcFace: Additive Angular Margin Loss for Deep Face Recognition
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Face generation is the task of generating (or interpolating) new faces from an existing dataset.
The state-of-the-art results for this task are located in the Image Generation parent.
<span style="color:grey; opacity: 0.6">( Image credit: Progressive Growing of GANs for Improved Quality, Stability, and Variation )</span>
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
Progressive Growing of GANs for Improved Quality, Stability, and Variation
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
GeneFace: Generalized and High-Fidelity Audio-Driven 3D Talking Face Synthesis
Progressive Growing of GANs for Improved Quality, Stability, and Variation
Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation
Interpreting the Latent Space of GANs for Semantic Face Editing
Towards Multi-domain Face Landmark Detection with Synthetic Data from Diffusion model
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
Progressive Growing of GANs for Improved Quality, Stability, and Variation
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.