AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
TL;DR
Sketch-text-driven rectified flow (STDRF), a conditional rectified-flow framework for identity-preserving and semantically controllable 4D face generation, and a sketch encoder enhanced by Geometric Contour and Texture Detail preprocessing and MixStyle domain adaptation are proposed.
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.
This work introduces CITA-Net, a novel identity-aware face editing architecture based on Stable Diffusion XL, and establishes a strong foundation for prompt-driven face understanding and enables practical applications such as forensic retrieval, semantic face editing, and natural language-based image search.
This work proposes RAGMesh, a retrieval-augmented framework that leverages text-correlated geometric priors to improve high-fidelity facial synthesis and editing, and introduces Adaptive RAG-guided Supervision (AdaRAGS), a region-aware constraint that explicitly aligns textual semantics with corresponding facial region...
The proposed sketch-guided face generation pipeline based on a Conditional Variational Autoencoder designed to generate facial reconstructions from sketches and conditional attributes uses a stochastic preprocessing pipeline to extract edge maps from facial photographs, reducing dependence on manually paired sketch-pho...
Identity-Consistent Expression Fields (ICEF) is proposed, a framework that explicitly disentangles a static, identity-specific radiance component from a dynamic, expression-conditioned deformation component, and introduces an identity preservation regularizer that constrains the deformation network to modify only expre...
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...
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