Face inpainting with diffusion models has recently achieved impressive visual quality, yet preserving identity fidelity under significant occlusion and conflicting text guidance remains a major challenge. To address this issue, we present Reference Semantic Inpainting for Face (ReSem-Face), a cascaded diffusion framework that introduces an explicit identity-conditioned semantic prior for multi-reference face inpainting. Our approach distills representative identity features from multiple references to reconstruct missing semantic regions, which then guide the diffusion process through a multi-stream conditioning architecture. This design provides strong semantic constraints when pixels are absent and stabilizes identity reconstruction while remaining compatible with prompt-driven edits. Experiments on CelebAHQ-IDI-5 and VGGFace2 demonstrate that ReSem-Face yields more reliable identity-preserving completion under severe semantic masks and improves text-controlled editing quality compared with representative baselines.
A diffusion-based framework with a stage-wise multi-condition guidance mechanism that enhances both structural and textural fidelity and compares with recent image-to-image translation and diffusion-based baselines to observe competitive performance in both visual coherence and identity preservation.
Yue Que, Xuegui Cheng, Shuqian Shi et al.· Neural Networks· 0 citations
Generative diffusion models have revolutionized facial image synthesis, yet robust identity preservation in high resolution outputs remains a critical challenge. This issue is especially vital for security systems, biometric authentication, and privacy sensitive applications, where any drift in identity integrity can u...
T. Rizwan, Sara Atito, Muhammad Awais et al.· arXiv.org· 0 citations
This work introduces ViDS, a Video Diffusion Shader that leverages 3D face tracking for expressive and identity-preserving portrait animation and introduces an autoregressive diffusion sampling process that extends generation beyond the model's native window while reducing discontinuities between adjacent clips.
Wenbo Ji, Davide Davoli, Zhe Chen et al.· arXiv.org· 0 citations
Experiments show that DBS achieves a better trade-off between facial fidelity and appearance consistency than existing open-source baselines, while providing a controllable basic framework for holistic identity modeling.
Yuxuan Xiao, Shanshan Zhang, Jian Yang et al.· arXiv.org· 1 citation
Results demonstrate the effectiveness of empirical reference statistics as a non-parametric prior for image inpainting by showing that the proposed method outperforms Mean Fill, Telea, and Navier-Stokes inpainting in PSNR, SSIM, and visual quality.
Jiaqi Kuang, Zihao Guo, Z. Qian· arXiv.org· 0 citations
RestoreGait is introduced, an end-to-end framework designed to actively recover occluded gait cues through a lightweight pseudo-3D spatiotemporal decoupled inpainting module that decouples spatial contour restoration from temporal motion aggregation, thereby effectively utilizing visible information across multiple fra...
Si-Wei Wei, Kun Yu, Ruo-Xi Wang et al.· Journal of Electronic Imagin...· 0 citations
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