Copertina

Structure-Guided Adversarial Training of Diffusion Models

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Yang, Ling, Qian, Haotian, Zhang, Zhilong, Liu, Jingwei, Cui, Bin
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Computer Vision and Pattern Recognition Artificial Intelligence Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Contextualized Diffusion Models for Text-Guided Image and Video Generation
di: Yang, Ling, et al.
Pubblicazione: (2024)

Improving Diffusion-Based Image Synthesis with Context Prediction
di: Yang, Ling, et al.
Pubblicazione: (2024)

Diffusion Models: A Comprehensive Survey of Methods and Applications
di: Yang, Ling, et al.
Pubblicazione: (2022)

Diffusion Adversarial Post-Training for One-Step Video Generation
di: Lin, Shanchuan, et al.
Pubblicazione: (2025)

Mastering Text-to-Image Diffusion: Recaptioning, Planning, and Generating with Multimodal LLMs
di: Yang, Ling, et al.
Pubblicazione: (2024)

RealCompo: Balancing Realism and Compositionality Improves Text-to-Image Diffusion Models
di: Zhang, Xinchen, et al.
Pubblicazione: (2024)

VideoGuide: Improving Video Diffusion Models without Training Through a Teacher's Guide
di: Lee, Dohun, et al.
Pubblicazione: (2024)

SPIE: Semantic and Structural Post-Training of Image Editing Diffusion Models with AI feedback
di: Benarous, Elior, et al.
Pubblicazione: (2025)

Adversarial Supervision Makes Layout-to-Image Diffusion Models Thrive
di: Li, Yumeng, et al.
Pubblicazione: (2024)

Improved Diffusion-based Generative Model with Better Adversarial Robustness
di: Wang, Zekun, et al.
Pubblicazione: (2025)

SDXL-Lightning: Progressive Adversarial Diffusion Distillation
di: Lin, Shanchuan, et al.
Pubblicazione: (2024)

Guiding Diffusion-based Reconstruction with Contrastive Signals for Balanced Visual Representation
di: Han, Boyu, et al.
Pubblicazione: (2026)

Personalized Federated Training of Diffusion Models with Privacy Guarantees
di: Patel, Kumar Kshitij, et al.
Pubblicazione: (2025)

Random Sampling for Diffusion-based Adversarial Purification
di: Zhang, Jiancheng, et al.
Pubblicazione: (2024)

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation
di: Monsefi, Amin Karimi, et al.
Pubblicazione: (2025)

Training Diffusion Models with Reinforcement Learning
di: Black, Kevin, et al.
Pubblicazione: (2023)

Pixel-Space Post-Training of Latent Diffusion Models
di: Zhang, Christina, et al.
Pubblicazione: (2024)

Leveraging Model Guidance to Extract Training Data from Personalized Diffusion Models
di: Wu, Xiaoyu, et al.
Pubblicazione: (2024)

Autoregressive Adversarial Post-Training for Real-Time Interactive Video Generation
di: Lin, Shanchuan, et al.
Pubblicazione: (2025)

AEGPO: Adaptive Entropy-Guided Policy Optimization for Diffusion Models
di: Li, Yuming, et al.
Pubblicazione: (2026)

Dense Optimizer : An Information Entropy-Guided Structural Search Method for Dense-like Neural Network Design
di: Tianyuan, Liu, et al.
Pubblicazione: (2024)

Fast Training of Diffusion Models with Masked Transformers
di: Zheng, Hongkai, et al.
Pubblicazione: (2023)

Towards Black-Box Membership Inference Attack for Diffusion Models
di: Li, Jingwei, et al.
Pubblicazione: (2024)

Enhancing Adversarial Transferability by Balancing Exploration and Exploitation with Gradient-Guided Sampling
di: Niu, Zenghao, et al.
Pubblicazione: (2025)

DiffusionNFT: Online Diffusion Reinforcement with Forward Process
di: Zheng, Kaiwen, et al.
Pubblicazione: (2025)

Instant Adversarial Purification with Adversarial Consistency Distillation
di: Lei, Chun Tong, et al.
Pubblicazione: (2024)

Autoguided Online Data Curation for Diffusion Model Training
di: Pais, Valeria, et al.
Pubblicazione: (2025)

RoPECraft: Training-Free Motion Transfer with Trajectory-Guided RoPE Optimization on Diffusion Transformers
di: Gokmen, Ahmet Berke, et al.
Pubblicazione: (2025)

Adversarially Trained Object Detector for Unsupervised Domain Adaptation
di: Fujii, Kazuma, et al.
Pubblicazione: (2021)

Consistent Diffusion Meets Tweedie: Training Exact Ambient Diffusion Models with Noisy Data
di: Daras, Giannis, et al.
Pubblicazione: (2024)

Self-Guided Generation of Minority Samples Using Diffusion Models
di: Um, Soobin, et al.
Pubblicazione: (2024)

DPAC: Distribution-Preserving Adversarial Control for Diffusion Sampling
di: Lee, Han-Jin, et al.
Pubblicazione: (2025)

VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs
di: Yang, Ling, et al.
Pubblicazione: (2023)

Shape-Guided Diffusion with Inside-Outside Attention
di: Park, Dong Huk, et al.
Pubblicazione: (2022)

DMin: Scalable Training Data Influence Estimation for Diffusion Models
di: Lin, Huawei, et al.
Pubblicazione: (2024)

DMQ: Dissecting Outliers of Diffusion Models for Post-Training Quantization
di: Lee, Dongyeun, et al.
Pubblicazione: (2025)

CKGAN: Training Generative Adversarial Networks Using Characteristic Kernel Integral Probability Metrics
di: Zhang, Kuntian, et al.
Pubblicazione: (2025)

SADA: Stability-guided Adaptive Diffusion Acceleration
di: Jiang, Ting, et al.
Pubblicazione: (2025)

Ambient Diffusion Posterior Sampling: Solving Inverse Problems with Diffusion Models Trained on Corrupted Data
di: Aali, Asad, et al.
Pubblicazione: (2024)

Learning Private Representations through Entropy-based Adversarial Training
di: Klein, Tassilo, et al.
Pubblicazione: (2025)