arXiv:2404.00597
공식 코드 · Papers with Code
Parameter and Data-Efficient Spectral StyleDCGAN
원문 초록
We present a simple, highly parameter, and data-efficient adversarial network for unconditional face generation. Our method: Spectral Style-DCGAN or SSD utilizes only 6.574 million parameters and 4739 dog faces from the Animal Faces HQ (AFHQ) dataset as training samples while preserving fidelity at low resolutions up to 64x64. Code available at https://github.com/Aryan-Garg/StyleDCGAN.
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FLUXSynID: A Framework for Identity-Controlled Synthetic Face Generation with Document and Live Images
MagicPortrait: Temporally Consistent Face Reenactment with 3D Geometric Guidance
ID-Booth: Identity-consistent Face Generation with Diffusion Models
FFaceNeRF: Few-shot Face Editing in Neural Radiance Fields
JoyGen: Audio-Driven 3D Depth-Aware Talking-Face Video Editing
DEGSTalk: Decomposed Per-Embedding Gaussian Fields for Hair-Preserving Talking Face Synthesis
토론
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