FastAvatar: 从单张无约束姿态图像快速重建高质量3D高斯点云人脸
FastAvatar: Instant 3D Gaussian Splatting for Faces from Single Unconstrained Poses
AI总结：
FastAvatar通过两阶段方法快速重建高质量3D人脸，实现逼真渲染与表情动画，提升单图像人脸重建效率与鲁棒性。
摘要：
我们提出了FastAvatar，一种用于单图像3D人脸重建的快速且稳健的算法，采用3D高斯点云（3DGS）技术。给定任意姿态的单张输入图像，FastAvatar在单块NVIDIA A100 GPU上约3秒内重建出高质量的完整头身3DGS人偶。我们采用两阶段设计：前馈编码器-解码器通过回归姿态不变身份嵌入的高斯结构预测粗略人脸几何，随后轻量级的测试阶段优化外观参数以实现逼真渲染。这种混合策略结合了直接预测的速度和稳定性与优化的准确性，即使在极端输入姿态下也能实现强大的身份保持。FastAvatar在运行速度超过现有每人优化方法（如FlashAvatar、GaussianAvatars、GASP）600倍的情况下，实现了最先进的重建质量（24.01 dB PSNR，0.91 SSIM）。重建完成后，我们的角色支持逼真的新视角合成和FLAME引导的表情动画，使从单张图像可控重现成为可能。通过联合提供高保真度、姿态鲁棒性和快速重建，FastAvatar显著扩展了基于3DGS的面部角色的应用范围。
英文摘要：
We present FastAvatar, a fast and robust algorithm for single-image 3D face reconstruction using 3D Gaussian Splatting (3DGS). Given a single input image from an arbitrary pose, FastAvatar recovers a high-quality, full-head 3DGS avatar in approximately 3 seconds on a single NVIDIA A100 GPU. We use a two-stage design: a feed-forward encoder-decoder predicts coarse face geometry by regressing Gaussian structure from a pose-invariant identity embedding, and a lightweight test-time refinement stage then optimizes the appearance parameters for photorealistic rendering. This hybrid strategy combines the speed and stability of direct prediction with the accuracy of optimization, enabling strong identity preservation even under extreme input poses. FastAvatar achieves state-of-the-art reconstruction quality (24.01 dB PSNR, 0.91 SSIM) while running over 600x faster than existing per-subject optimization methods (e.g., FlashAvatar, GaussianAvatars, GASP). Once reconstructed, our avatars support photorealistic novel-view synthesis and FLAME-guided expression animation, enabling controllable reenactment from a single image. By jointly offering high fidelity, robustness to pose, and rapid reconstruction, FastAvatar significantly broadens the applicability of 3DGS-based facial avatars.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
