Image de couverture de livre

CCDM: Continuous Conditional Diffusion Models for Image Generation

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Ding, Xin, Wang, Yongwei, Zhang, Kao, Wang, Z. Jane
Format:	Preprint
Publié:	2024
Sujets:	Computer Vision and Pattern Recognition Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Turning Waste into Wealth: Leveraging Low-Quality Samples for Enhancing Continuous Conditional Generative Adversarial Networks
par: Ding, Xin, et autres
Publié: (2023)

Imbalance-Robust and Sampling-Efficient Continuous Conditional GANs via Adaptive Vicinity and Auxiliary Regularization
par: Ding, Xin, et autres
Publié: (2025)

Enhancing Diffusion-Based Quantitatively Controllable Image Generation via Matrix-Form EDM and Adaptive Vicinal Training
par: Ding, Xin, et autres
Publié: (2026)

Towards Controllable Image Generation through Representation-Conditioned Diffusion Models
par: Karthikeyan, Nithesh Chandher, et autres
Publié: (2026)

Semantic-Guided Generative Image Augmentation Method with Diffusion Models for Image Classification
par: Li, Bohan, et autres
Publié: (2023)

Exploring Time Conditioning in Diffusion Generative Models from Disjoint Noisy Data Manifolds
par: Li, Liuzhuozheng, et autres
Publié: (2026)

Conditional Balance: Improving Multi-Conditioning Trade-Offs in Image Generation
par: Cohen, Nadav Z., et autres
Publié: (2024)

MADFormer: Mixed Autoregressive and Diffusion Transformers for Continuous Image Generation
par: Chen, Junhao, et autres
Publié: (2025)

OmniControlNet: Dual-stage Integration for Conditional Image Generation
par: Wang, Yilin, et autres
Publié: (2024)

Quaternion Wavelet-Conditioned Diffusion Models for Image Super-Resolution
par: Sigillo, Luigi, et autres
Publié: (2025)

DreamSteerer: Enhancing Source Image Conditioned Editability using Personalized Diffusion Models
par: Yu, Zhengyang, et autres
Publié: (2024)

Empirical Evidences for the Effects of Feature Diversity in Open Set Recognition and Continual Learning
par: Xu, Jiawen, et autres
Publié: (2025)

Continual Personalization for Diffusion Models
par: Liao, Yu-Chien, et autres
Publié: (2025)

Generative Diffusion Modeling: A Practical Handbook
par: Ding, Zihan, et autres
Publié: (2024)

Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing
par: Wu, Sihao, et autres
Publié: (2025)

Diffusion Model Conditioning on Gaussian Mixture Model and Negative Gaussian Mixture Gradient
par: Lu, Weiguo, et autres
Publié: (2024)

Optical Diffusion Models for Image Generation
par: Oguz, Ilker, et autres
Publié: (2024)

Representation-Conditioned Diffusion Models for Guided Training Data Generation
par: Karthikeyan, Nithesh Chandher, et autres
Publié: (2026)

Global Context with Discrete Diffusion in Vector Quantised Modelling for Image Generation
par: Hu, Minghui, et autres
Publié: (2021)

Giving a Hand to Diffusion Models: a Two-Stage Approach to Improving Conditional Human Image Generation
par: Pelykh, Anton, et autres
Publié: (2024)

Flash Diffusion: Accelerating Any Conditional Diffusion Model for Few Steps Image Generation
par: Chadebec, Clément, et autres
Publié: (2024)

Canonical Latent Representations in Conditional Diffusion Models
par: Xu, Yitao, et autres
Publié: (2025)

Efficient Conditional Diffusion Model with Probability Flow Sampling for Image Super-resolution
par: Yuan, Yutao, et autres
Publié: (2024)

Conditional Diffusion Models are Medical Image Classifiers that Provide Explainability and Uncertainty for Free
par: Favero, Gian Mario, et autres
Publié: (2025)

Anomaly-Preference Image Generation
par: Wang, Fuyun, et autres
Publié: (2026)

Generative Diffusion Augmentation with Quantum-Enhanced Discrimination for Medical Image Diagnosis
par: Xia, Jingsong, et autres
Publié: (2026)

AdvAD: Exploring Non-Parametric Diffusion for Imperceptible Adversarial Attacks
par: Li, Jin, et autres
Publié: (2025)

Compositional Image Decomposition with Diffusion Models
par: Su, Jocelin, et autres
Publié: (2024)

High-Fidelity Text-to-Image Generation from Pre-Trained Vision-Language Models via Distribution-Conditioned Diffusion Decoding
par: Hong, Ji Woo, et autres
Publié: (2026)

Data Pruning in Generative Diffusion Models
par: Briq, Rania, et autres
Publié: (2024)

CookingDiffusion: Cooking Procedural Image Generation with Stable Diffusion
par: Wang, Yuan, et autres
Publié: (2025)

Edify Image: High-Quality Image Generation with Pixel Space Laplacian Diffusion Models
par: NVIDIA, et autres
Publié: (2024)

Unsupervised Raindrop Removal from a Single Image using Conditional Diffusion Models
par: Fazry, Lhuqita, et autres
Publié: (2025)

Input-Adaptive Generative Dynamics in Diffusion Models
par: Xing, Yucheng, et autres
Publié: (2024)

CLoG: Benchmarking Continual Learning of Image Generation Models
par: Zhang, Haotian, et autres
Publié: (2024)

Post-training Quantization for Text-to-Image Diffusion Models with Progressive Calibration and Activation Relaxing
par: Tang, Siao, et autres
Publié: (2023)

Radioactive Watermarks in Diffusion and Autoregressive Image Generative Models
par: Meintz, Michel, et autres
Publié: (2025)

Environment-Aware Satellite Image Generation with Diffusion Models
par: Kostagiolas, Nikos, et autres
Publié: (2025)

Marigold: Affordable Adaptation of Diffusion-Based Image Generators for Image Analysis
par: Ke, Bingxin, et autres
Publié: (2025)

Towards Understanding the Working Mechanism of Text-to-Image Diffusion Model
par: Yi, Mingyang, et autres
Publié: (2024)