This paper presents TriAnchor-ID, a prototype framework for identity-conditioned diffusion portrait generation. The work focuses on multi-view semantic identity anchoring using ArcFace/InsightFace embeddings, quality-weighted identity aggregation, landmark-derived geometric observations, and post-generation identity consistency evaluation. The paper corrects an important distinction between semantic face identity embeddings and physical 3D morphable model parameters: the implemented 512-dimensional ArcFace vector is treated as a semantic identity anchor, not as a FLAME or 3DMM shape vector. The proposed Identity Capsule design separates implemented components from future extensions such as FLAME/DECA shape fitting, UV texture modeling, spatial ControlNet conditioning, and inference-time identity consistency guidance. This version is released as a preprint/prototype research report. The qualitative examples are illustrative, and the paper outlines a controlled evaluation protocol using ArcFace similarity, identity drift score, landmark error, face detection failure rate, prompt alignment, repeated seeds, and confidence intervals.
Akash Kumar (Tue,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: