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MVCHead is a novel method for generating 3D Gaussian head avatars from single 2D images without multi-view data, using hierarchical state space models and multi-view consistency enforcement.
FFAvatar proposes a feed-forward framework for reconstructing high-quality, animatable 3D Gaussian head avatars from few unposed images in seconds, achieving a 5.5 PSNR improvement over state-of-the-art on the NeRSemble benchmark.