HYDRO: Towards Non-Reversible Face De-Identification Using a High-Fidelity Hybrid Diffusion and Target-Oriented Approach

arXiv:2609.27011 · cs.CV · Submitted 2026-09-22 · Read on arXiv

cs.CV

Submitted: 2026-09-22

Updated: 2026-09-22

Terminology

• Fidelity — 39× in this paper · explained in 2 episodes
• Diffusion Model — 36× in this paper · explained in 8 episodes
• Ablation — 13× in this paper · explained in 1 episode
• Conference on Computer Vision and Pattern Recognition — 13× in this paper
• Diffusion Process — 13× in this paper · explained in 2 episodes
• Eye Similarity Discriminator — 8× in this paper
• Diffusion Models — 6× in this paper · explained in 6 episodes
• Loss Function — 6× in this paper · explained in 2 episodes
• Regularization — 6× in this paper · explained in 3 episodes
• Robustness — 6× in this paper · explained in 5 episodes
• Trace — 6× in this paper · explained in 2 episodes
• Alignment — 5× in this paper · explained in 1 episode
• Ablation Studies — 4× in this paper · explained in 1 episode
• Cosine Similarity — 4× in this paper · explained in 3 episodes
• Latent Space — 3× in this paper · explained in 7 episodes
• Transformer — 3× in this paper · explained in 2 episodes
• Ablation study — 2× in this paper · explained in 1 episode
• Actor — 2× in this paper · explained in 3 episodes
• Adversarial Training — 2× in this paper · explained in 1 episode
• Distillation — 2× in this paper · explained in 2 episodes
• Embeddings — 2× in this paper · explained in 2 episodes
• Knowledge Distillation — 2× in this paper · explained in 11 episodes
• U-net architecture — 2× in this paper · explained in 3 episodes
• Adversarial Model — 1× in this paper · explained in 1 episode
• Adversarial Noise — 1× in this paper · explained in 1 episode
• Alignment Problem — 1× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Clustering — 1× in this paper · explained in 2 episodes
• Computational overhead — 1× in this paper · explained in 2 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Downstream Tasks — 1× in this paper · explained in 2 episodes
• European Association for Biometrics — 1× in this paper
• False Acceptance Rates — 1× in this paper
• Generative AI — 1× in this paper · explained in 2 episodes
• Generative Adversarial Networks (GANs) — 1× in this paper · explained in 3 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Identity Tracking Module — 1× in this paper
• International Conference on Pattern Recognition — 1× in this paper
• Labeled Faces in the Wild — 1× in this paper
• Latent Diffusion Model — 1× in this paper · explained in 2 episodes
• Latent Diffusion Models — 1× in this paper · explained in 2 episodes
• Multi-Layer Perceptron — 1× in this paper
• Nash Equilibrium — 1× in this paper · explained in 2 episodes
• Self-Supervised Learning — 1× in this paper · explained in 7 episodes
• Winter Conference on Applications of Computer Vision — 1× in this paper

Sources

• CFA-Net: Controllable Face Anonymization Network with Identity Representation Manipulation
• Latent Diffusion Models for Attribute-Preserving Image Anonymization
• IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models
• Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour
• DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models
• Geometric GAN
• Decoupled Weight Decay Regularization
• An Improved Evaluation Framework for Generative Adversarial Networks

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