Loki replaces RGB conditioning stacks with identity-orthogonal parametric face encodings rasterized for diffusion, achieving efficient cross-ID portrait animation without cross-ID training data.
arXiv preprint arXiv:2404.04104 , year=
5 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 5verdicts
UNVERDICTED 5representative citing papers
Four-stage pipeline reconstructs explicit facial hair strands from multi-view images via 3D Gaussian optimization and curve tracing, claimed as first such method.
TOPOS creates high-fidelity 3D heads with fixed industry topology from single images via a specialized VAE with Perceiver Resampler and a rectified flow transformer.
A single-image head reconstruction method uses coarse-to-fine optimization with normal consistency, landmarks, and geometry-aware constraints on curvature and conformality to produce meshes with industry-grade topology and preserved facial identity.
SuperFace refines ARKit facial expression estimation by using human preference feedback on rendered faces to optimize beyond noisy pseudo-label supervision from capture software.
citing papers explorer
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Loki: Representation over Architecture for Diffusion-Based Portrait Animation
Loki replaces RGB conditioning stacks with identity-orthogonal parametric face encodings rasterized for diffusion, achieving efficient cross-ID portrait animation without cross-ID training data.
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Wispy to Voluminous: Prior-free Multi-view Capture of Strand-level Facial Hair
Four-stage pipeline reconstructs explicit facial hair strands from multi-view images via 3D Gaussian optimization and curve tracing, claimed as first such method.
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TOPOS: High-Fidelity and Efficient Industry-Grade 3D Head Generation
TOPOS creates high-fidelity 3D heads with fixed industry topology from single images via a specialized VAE with Perceiver Resampler and a rectified flow transformer.
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High-Fidelity Single-Image Head Modeling with Industry-Grade Topology
A single-image head reconstruction method uses coarse-to-fine optimization with normal consistency, landmarks, and geometry-aware constraints on curvature and conformality to produce meshes with industry-grade topology and preserved facial identity.
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SuperFace: Preference-Aligned Facial Expression Estimation Beyond Pseudo Supervision
SuperFace refines ARKit facial expression estimation by using human preference feedback on rendered faces to optimize beyond noisy pseudo-label supervision from capture software.