Cover Image

How Diffusion Models Memorize

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Kim, Juyeop, Kim, Songkuk, Lee, Jong-Seok
Format:	Preprint
Published:	2025
Subjects:	Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Steering Away from Memorization: Reachability-Constrained Reinforcement Learning for Text-to-Image Diffusion
by: Karnik, Sathwik, et al.
Published: (2026)

Impact of Regularization on Calibration and Robustness: from the Representation Space Perspective
by: Park, Jonghyun, et al.
Published: (2024)

DebFilter: Eradicating Biases Stashed in Value
by: Lee, Seung Hyuk, et al.
Published: (2026)

Sparsity as a Key: Unlocking New Insights from Latent Structures for Out-of-Distribution Detection
by: Oh, Ahyoung, et al.
Published: (2026)

DESSERT: Diffusion-based Event-driven Single-frame Synthesis via Residual Training
by: Kong, Jiyun, et al.
Published: (2025)

Adjusting Initial Noise to Mitigate Memorization in Text-to-Image Diffusion Models
by: Han, Hyeonggeun, et al.
Published: (2025)

Mosaic: Compositional Multi-Concept Erasure via Vector Field Blending
by: Ko, Junseok, et al.
Published: (2026)

Progressive Learned Image Compression for Machine Perception
by: Kim, Jungwoo, et al.
Published: (2025)

Coarse-to-Fine: Progressive Image Compression for Semantically Hierarchical Classification
by: Kim, Jungwoo, et al.
Published: (2026)

Investigating Memorization in Video Diffusion Models
by: Chen, Chen, et al.
Published: (2024)

Towards Memorization-Free Diffusion Models
by: Chen, Chen, et al.
Published: (2024)

Low-Cost Self-Ensembles Based on Multi-Branch Transformation and Grouped Convolution
by: Lee, Hojung, et al.
Published: (2024)

Memorization In Stable Diffusion Is Unexpectedly Driven by CLIP Embeddings
by: Kim, Bumjun, et al.
Published: (2026)

Detecting, Explaining, and Mitigating Memorization in Diffusion Models
by: Wen, Yuxin, et al.
Published: (2024)

SLIM: Semantic-based Low-bitrate Image compression for Machines by leveraging diffusion
by: Lee, Hyeonjin, et al.
Published: (2025)

Diffusion Model for Dense Matching
by: Nam, Jisu, et al.
Published: (2023)

Redistribute Ensemble Training for Mitigating Memorization in Diffusion Models
by: Guan, Xiaoliu, et al.
Published: (2025)

Filtering Memorization from Parameter-Space in Diffusion Models
by: Zhe, Yu, et al.
Published: (2026)

Key-point Guided Deformable Image Manipulation Using Diffusion Model
by: Oh, Seok-Hwan, et al.
Published: (2024)

On Memorization in Diffusion Models
by: Gu, Xiangming, et al.
Published: (2023)

Network Fission Ensembles for Low-Cost Self-Ensembles
by: Lee, Hojung, et al.
Published: (2024)

Anomaly Score: Evaluating Generative Models and Individual Generated Images based on Complexity and Vulnerability
by: Hwang, Jaehui, et al.
Published: (2023)

SC-Pro: Training-Free Framework for Defending Unsafe Image Synthesis Attack
by: Park, Junha, et al.
Published: (2025)

When Model Knowledge meets Diffusion Model: Diffusion-assisted Data-free Image Synthesis with Alignment of Domain and Class
by: Kim, Yujin, et al.
Published: (2025)

Enhancing Privacy-Utility Trade-offs to Mitigate Memorization in Diffusion Models
by: Chen, Chen, et al.
Published: (2025)

MemBench: Memorized Image Trigger Prompt Dataset for Diffusion Models
by: Hong, Chunsan, et al.
Published: (2024)

Broken Memories: Detecting and Mitigating Memorization in Diffusion Models with Degraded Generations
by: Huang, Yuanmin, et al.
Published: (2026)

Exploring Local Memorization in Diffusion Models via Bright Ending Attention
by: Chen, Chen, et al.
Published: (2024)

Construction of Digital Terrain Maps from Multi-view Satellite Imagery using Neural Volume Rendering
by: Biberstein, Josef X., et al.
Published: (2025)

Hybrid Video Diffusion Models with 2D Triplane and 3D Wavelet Representation
by: Kim, Kihong, et al.
Published: (2024)

Grid Diffusion Models for Text-to-Video Generation
by: Lee, Taegyeong, et al.
Published: (2024)

Demystifying Foreground-Background Memorization in Diffusion Models
by: Di, Jimmy Z., et al.
Published: (2025)

An Inversion-based Measure of Memorization for Diffusion Models
by: Ma, Zhe, et al.
Published: (2024)

PoseBridge: Bridging the Skeletonization Gap for Zero-Shot Skeleton-Based Action Recognition
by: Lee, Sanghyeon, et al.
Published: (2026)

How to Move Your Dragon: Text-to-Motion Synthesis for Large-Vocabulary Objects
by: Lee, Wonkwang, et al.
Published: (2025)

Rethinking Token Reduction for Diffusion Models via Output-Similarity-Awareness
by: Lee, Hangyeol, et al.
Published: (2026)

RAD: Region-Aware Diffusion Models for Image Inpainting
by: Kim, Sora, et al.
Published: (2024)

Modeling Visual Memorability Assessment with Autoencoders Reveals Characteristics of Memorable Images
by: Bagheri, Elham, et al.
Published: (2024)

Adaptive Explicit Knowledge Transfer for Knowledge Distillation
by: Park, Hyungkeun, et al.
Published: (2024)

Capacity Control is an Effective Memorization Mitigation Mechanism in Text-Conditional Diffusion Models
by: Dutt, Raman, et al.
Published: (2024)