Sun, G.[Gan],
Liang, W.Q.[Wen-Qi],
Dong, J.H.[Jia-Hua],
Li, J.[Jun],
Ding, Z.M.[Zheng-Ming],
Cong, Y.[Yang],
Create Your World: Lifelong Text-to-Image Diffusion,
PAMI(46), No. 9, September 2024, pp. 6454-6470.
IEEE DOI
2408
Task analysis, Dogs, Computational modeling, Semantics, Training,
Neural networks, Continual learning, image generation,
stable diffusion
BibRef
Verma, A.[Ayushi],
Badal, T.[Tapas],
Bansal, A.[Abhay],
Advancing Image Generation with Denoising Diffusion Probabilistic
Model and ConvNeXt-V2:
A novel approach for enhanced diversity and quality,
CVIU(247), 2024, pp. 104077.
Elsevier DOI
2408
Deep learning, Diffusion model, Generative model, Image generation
BibRef
Ren, J.X.[Jia-Xin],
Liu, W.Z.[Wan-Zeng],
Chen, J.[Jun],
Yin, S.X.[Shun-Xi],
Tao, Y.[Yuan],
Word2Scene: Efficient remote sensing image scene generation with only
one word via hybrid intelligence and low-rank representation,
PandRS(218), 2024, pp. 231-257.
Elsevier DOI Code:
WWW Link.
2412
Award, U.V. Helava, ISPRS. Intelligentized surveying and mapping, Hybrid intelligence,
Remote sensing image scene generation, Diffusion models, Zero-shot learning
BibRef
Ridley, H.[Henrietta],
Alcover-Couso, R.[Roberto],
SanMiguel, J.C.[Juan C.],
Controlling semantics of diffusion-augmented data for unsupervised
domain adaptation,
IET-CV(19), No. 1, 2025, pp. e70002.
DOI Link Code:
WWW Link.
2502
image segmentation, unsupervised learning
BibRef
Wang, W.L.[Wei-Lun],
Bao, J.M.[Jian-Min],
Zhou, W.G.[Wen-Gang],
Chen, D.D.[Dong-Dong],
Chen, D.[Dong],
Yuan, L.[Lu],
Li, H.Q.[Hou-Qiang],
SinDiffusion: Learning a Diffusion Model from a Single Natural Image,
PAMI(47), No. 5, May 2025, pp. 3412-3423.
IEEE DOI
2504
Diffusion models, Image synthesis, Training, Noise reduction,
Periodic structures, Translation, Mathematical models, Art, Noise,
image manipulation
BibRef
Kim, J.[Jisoo],
Kang, J.[Jiwoo],
Kim, T.[Taewan],
Oh, H.[Heeseok],
SinWaveFusion: Learning a single image diffusion model in wavelet
domain,
IVC(159), 2025, pp. 105551.
Elsevier DOI
2505
Single image generation, Denoising diffusion models, Wavelet transform
BibRef
Huang, Y.W.[Ya-Wen],
Huang, H.M.[Hui-Min],
Zheng, H.[Hao],
Li, Y.X.[Yue-Xiang],
Zheng, F.[Feng],
Zhen, X.T.[Xian-Tong],
Zheng, Y.F.[Ye-Feng],
Learning to Generalize Heterogeneous Representation for Cross-Modality
Image Synthesis via Multiple Domain Interventions,
IJCV(133), No. 7, July 2025, pp. 4727-4748.
Springer DOI
2506
BibRef
Zhang, Z.[Ziyi],
Zhang, S.[Sen],
Shen, L.[Li],
Zhan, Y.B.[Yi-Bing],
Luo, Y.[Yong],
Hu, H.[Han],
Du, B.[Bo],
Wen, Y.G.[Yong-Gang],
Tao, D.C.[Da-Cheng],
Aligning Text-to-Image Diffusion Models With Constrained
Reinforcement Learning,
PAMI(47), No. 11, November 2025, pp. 9550-9562.
IEEE DOI
2510
Optimization, Diffusion models, Noise reduction, Text to image,
Neurons, Reinforcement learning, constrained optimization
BibRef
Zhang, Z.[Ziyi],
Shen, L.[Li],
Zhang, S.[Sen],
Ye, D.[Deheng],
Luo, Y.[Yong],
Shi, M.J.[Miao-Jing],
Shan, D.J.[Dong-Jing],
Du, B.[Bo],
Tao, D.C.[Da-Cheng],
Aligning Few-Step Diffusion Models With Dense Reward Difference
Learning,
PAMI(48), No. 7, July 2026, pp. 7375-7386.
IEEE DOI
2606
Trajectory, Noise reduction, Diffusion models, Optimization, Standards,
Noise, Training, Noise measurement, Text to image, dense rewards
BibRef
Zhu, J.Y.[Jing-Yuan],
Ma, H.M.[Hui-Min],
Chen, J.S.[Jian-Sheng],
Yuan, J.[Jian],
DomainStudio: Fine-Tuning Diffusion Models for Domain-Driven Image
Generation Using Limited Data,
IJCV(133), No. 10, October 2025, pp. 7012-7036.
Springer DOI
2511
BibRef
Xiang, X.[Xin],
Zhou, W.H.[Wen-Hui],
Zhu, H.N.[Hao-Nan],
Li, Y.[Yunrui],
Dai, G.J.[Guo-Jun],
Lin, L.[Lili],
EEG-driven natural image reconstruction with regional semantic
awareness,
PR(172), 2026, pp. 112589.
Elsevier DOI Code:
WWW Link.
2601
Reconstruct visual stimuli from electroencephalography (EEG) signals.
EEG, Visual stimuli, Latent diffusion model,
Image reconstruction, Regional semantic awareness, Joint learning
BibRef
Mao, Z.D.[Zhen-Dong],
Huang, M.Q.[Meng-Qi],
Ding, F.[Fei],
Liu, M.C.[Ming-Cong],
He, Q.[Qian],
Zhang, Y.D.[Yong-Dong],
RealCustom++: Representing Images as Real Textual Word for Real-Time
Customization,
PAMI(48), No. 2, February 2026, pp. 2078-2095.
IEEE DOI
2601
BibRef
Earlier: A2, A1, A4, A5, A6, Only:
RealCustom: Narrowing Real Text Word for Real-Time Open-Domain
Text-to-Image Customization,
CVPR24(7476-7485)
IEEE DOI
2410
Controllability, Training, Semantics, Overfitting, Visualization,
Toy manufacturing industry, Text to image, Navigation, curriculum learning.
Adaptive systems, Limiting, text-to-image generation, diffusion models
BibRef
Ni, Z.[Zanlin],
Wang, Y.L.[Yu-Lin],
Hua, Y.[Yeguo],
Zhou, R.P.[Ren-Ping],
Guo, J.Y.[Jia-Yi],
Song, J.[Jun],
Zheng, B.[Bo],
Huang, G.[Gao],
AdaGen: Learning Adaptive Policy for Image Synthesis,
PAMI(48), No. 3, March 2026, pp. 2695-2713.
IEEE DOI
2602
Adaptation models, Predictive models, Image synthesis,
Diffusion models, Iterative methods, Generators,
iterative generation models
BibRef
Guo, J.[Junyi],
Chen, H.J.[Hong-Jun],
Wang, Q.F.[Qiu-Feng],
Chen, Y.[Yaran],
Cheng, G.L.[Guang-Liang],
Wu, F.Y.[Fang-Yu],
Lim, E.G.[Eng Gee],
EmoSENSE: Modeling Sentiment-Semantic Knowledge With Hierarchical
Reinforcement Learning for Emotional Image Generation,
AffCom(17), No. 2, April 2026, pp. 1806-1822.
IEEE DOI
2606
Image synthesis, Semantics, Visualization, Correlation,
Reinforcement learning, Adaptation models, Affective computing
BibRef
Fuest, M.[Michael],
Ma, P.[Pingchuan],
Gui, M.[Ming],
Schusterbauer, J.[Johannes],
Hu, V.T.[Vincent Tao],
Ommer, B.[Björn],
Diffusion Models and Representation Learning: A Survey,
PAMI(48), No. 7, July 2026, pp. 7209-7228.
IEEE DOI
2606
Diffusion models, Representation learning, Noise, Noise reduction,
Surveys, Noise measurement, Training, Neural networks, Taxonomy,
representation learning
BibRef
Wang, Y.B.[Ya-Bin],
Hong, X.P.[Xiao-Peng],
Ma, Z.H.[Zhi-Heng],
Su, Z.[Zhou],
Zhang, J.P.[Jin-Peng],
Huang, Z.W.[Zhi-Wu],
Continual Conceptual Entity Learning for Text-to-Image Generative
Models,
MultMed(28), 2026, pp. 5785-5797.
IEEE DOI
2607
Text to image, Training, Diffusion models, Adaptation models,
Generators, Data models, Noise reduction, Interference
BibRef
Dubey, A.[Adarsh],
Sharma, M.[Mridul],
Kancharla, P.[Parimala],
Selective subspace unlearning for text to image diffusion models,
PRL(207), 2026, pp. 260-265.
Elsevier DOI
2608
Machine unlearning, Nash bargaining, Text-to-image, Concept erasing
BibRef
Zhu, Y.F.[Yi-Fan],
Wang, C.J.[Cheng-Jia],
Dong, X.H.[Xing-Hui],
UMDM-USG: A unified multi-view diffusion model for underwater scene
generation via cross-view representation alignment,
PR(180), 2026, pp. 114232.
Elsevier DOI
2608
Multi-view learning, Cross-view representation alignment,
Underwater scene generation, Diffusion model, Dense prediction
BibRef
Dong, S.[Sibo],
Shaheen, I.[Ismail],
Shen, M.[Maggie],
Mallick, R.[Rupayan],
Bargal, S.A.[Sarah Adel],
ViSTA: Visual Storytelling using Multi-modal Adapters for
Text-to-Image Diffusion Models,
WACV26(12-21)
IEEE DOI
2609
Protocols, Amplitude shift keying, LoRa, Videos, story generation,
multimodal learning
BibRef
Hu, Z.J.[Zi-Jing],
Zhang, F.D.[Feng-Da],
Chen, L.[Long],
Kuang, K.[Kun],
Li, J.H.[Jia-Hui],
Gao, K.[Kaifeng],
Xiao, J.[Jun],
Wang, X.[Xin],
Zhu, W.W.[Wen-Wu],
Towards Better Alignment: Training Diffusion Models with
Reinforcement Learning Against Sparse Rewards,
CVPR25(23604-23614)
IEEE DOI
2508
Training, Codes, Noise reduction, Text to image,
Reinforcement learning, Diffusion models, Optimization
BibRef
Ye, Z.[Zilyu],
Chen, Z.Y.[Zhi-Yang],
Li, T.C.[Tian-Cheng],
Huang, Z.[Zemin],
Luo, W.J.[Wei-Jian],
Qi, G.J.[Guo-Jun],
Schedule On the Fly: Diffusion Time Prediction for Faster and Better
Image Generation,
CVPR25(23412-23422)
IEEE DOI
2508
Image quality, Schedules, Image synthesis, Noise reduction, Noise,
Text to image, Reinforcement learning, Diffusion models, Noise level
BibRef
Thakral, K.[Kartik],
Glaser, T.[Tamar],
Hassner, T.[Tal],
Vatsa, M.[Mayank],
Singh, R.[Richa],
Fine-Grained Erasure in Text-To-Image Diffusion-Based Foundation
Models,
CVPR25(9121-9130)
IEEE DOI
2508
Manifolds, Foundation models, Computational modeling, Semantics,
Text to image, Dogs, Flowering plants, Diffusion models, unlearning,
diffusion
BibRef
Jun, Y.[Youngjun],
Park, J.[Jiwoo],
Choo, K.[Kyobin],
Choi, T.E.[Tae Eun],
Hwang, S.J.[Seong Jae],
Disentangling Disentangled Representations: Towards Improved Latent
Units via Diffusion Models,
WACV25(3559-3569)
IEEE DOI
2505
Training, Disentangled representation learning, Semantics, Noise reduction,
Stochastic processes, Focusing, Transforms, diffusion models
BibRef
Zhang, J.Y.[Jian-Yi],
Zhou, Y.F.[Yu-Fan],
Gu, J.X.[Jiu-Xiang],
Wigington, C.[Curtis],
Yu, T.[Tong],
Chen, Y.R.[Yi-Ran],
Sun, T.[Tong],
Zhang, R.[Ruiyi],
ARTIST: Improving the Generation of Text-Rich Images with
Disentangled Diffusion Models and Large Language Models,
WACV25(1268-1278)
IEEE DOI
2505
Training, Visualization, Accuracy, Image synthesis,
Large language models, Disentangled representation learning,
Rendering (computer graphics)
BibRef
Butt, M.A.[Muhammad Atif],
Wang, K.[Kai],
Vazquez-Corral, J.[Javier],
van de Weijer, J.[Joost],
ColorPeel: Color Prompt Learning with Diffusion Models via Color and
Shape Disentanglement,
ECCV24(VII: 456-472).
Springer DOI
2412
Project:
WWW Link.
BibRef
Zhang, D.J.H.[David Jun-Hao],
Xu, M.[Mutian],
Wu, J.Z.J.[Jay Zhang-Jie],
Xue, C.[Chuhui],
Zhang, W.Q.[Wen-Qing],
Han, X.G.[Xiao-Guang],
Bai, S.[Song],
Shou, M.Z.[Mike Zheng],
Free-atm: Harnessing Free Attention Masks for Representation Learning
on Diffusion-generated Images,
ECCV24(XL: 465-482).
Springer DOI
2412
BibRef
Hudson, D.A.[Drew A.],
Zoran, D.[Daniel],
Malinowski, M.[Mateusz],
Lampinen, A.K.[Andrew K.],
Jaegle, A.[Andrew],
McClelland, J.L.[James L.],
Matthey, L.[Loic],
Hill, F.[Felix],
Lerchner, A.[Alexander],
SODA: Bottleneck Diffusion Models for Representation Learning,
CVPR24(23115-23127)
IEEE DOI
2410
Representation learning, Training, Visualization, Image synthesis,
Semantics, Noise reduction, Self-supervised learning, classification
BibRef
Miao, Z.C.[Zi-Chen],
Wang, J.[Jiang],
Wang, Z.[Ze],
Yang, Z.Y.[Zheng-Yuan],
Wang, L.J.[Li-Juan],
Qiu, Q.[Qiang],
Liu, Z.C.[Zi-Cheng],
Training Diffusion Models Towards Diverse Image Generation with
Reinforcement Learning,
CVPR24(10844-10853)
IEEE DOI
2410
Training, Gradient methods, Limiting, Image synthesis, Estimation,
Diffusion processes, Reinforcement learning
BibRef
Zhu, R.[Rui],
Pan, Y.W.[Ying-Wei],
Li, Y.[Yehao],
Yao, T.[Ting],
Sun, Z.L.[Zheng-Long],
Mei, T.[Tao],
Chen, C.W.[Chang Wen],
SD-DiT: Unleashing the Power of Self-Supervised Discrimination in
Diffusion Transformer*,
CVPR24(8435-8445)
IEEE DOI
2410
Training, Image synthesis, Noise, Diffusion processes,
Ordinary differential equations, Transformers, self-supervised learning
BibRef
Deng, F.[Fei],
Wang, Q.F.[Qi-Fei],
Wei, W.[Wei],
Hou, T.B.[Ting-Bo],
Grundmann, M.[Matthias],
PRDP: Proximal Reward Difference Prediction for Large-Scale Reward
Finetuning of Diffusion Models,
CVPR24(7423-7433)
IEEE DOI
2410
Training, Technological innovation, Closed box,
Reinforcement learning, Diffusion models, RLHF
BibRef
Yu, Y.Y.[Yu-Yang],
Liu, B.Z.[Bang-Zhen],
Zheng, C.X.[Chen-Xi],
Xu, X.M.[Xue-Miao],
He, S.F.[Sheng-Feng],
Zhang, H.D.[Huai-Dong],
Beyond Textual Constraints: Learning Novel Diffusion Conditions with
Fewer Examples,
CVPR24(7109-7118)
IEEE DOI Code:
WWW Link.
2410
Training, Adaptation models, Codes, Text to image,
Diffusion processes, Diffusion models, diffusion model
BibRef
Dalva, Y.[Yusuf],
Yanardag, P.[Pinar],
NoiseCLR: A Contrastive Learning Approach for Unsupervised Discovery
of Interpretable Directions in Diffusion Models,
CVPR24(24209-24218)
IEEE DOI
2410
Image synthesis, Computational modeling, Semantics, Text to image,
Contrastive learning, Diffusion models,
semantic discovery
BibRef
Luo, G.[Grace],
Darrell, T.J.[Trevor J.],
Wang, O.[Oliver],
Goldman, D.B.[Dan B],
Holynski, A.[Aleksander],
Readout Guidance: Learning Control from Diffusion Features,
CVPR24(8217-8227)
IEEE DOI Code:
WWW Link.
2410
Training, Head, Image edge detection, Training data, Text to image,
Diffusion models, Image and video synthesis and generation
BibRef
Wallace, B.[Bram],
Dang, M.[Meihua],
Rafailov, R.[Rafael],
Zhou, L.Q.[Lin-Qi],
Lou, A.[Aaron],
Purushwalkam, S.[Senthil],
Ermon, S.[Stefano],
Xiong, C.M.[Cai-Ming],
Joty, S.[Shafiq],
Naik, N.[Nikhil],
Diffusion Model Alignment Using Direct Preference Optimization,
CVPR24(8228-8238)
IEEE DOI
2410
Training, Learning systems, Visualization, Pipelines, Text to image,
Reinforcement learning, Diffusion models, generative, diffusion, dpo
BibRef
Gokaslan, A.[Aaron],
Cooper, A.F.[A. Feder],
Collins, J.[Jasmine],
Seguin, L.[Landan],
Jacobson, A.[Austin],
Patel, M.[Mihir],
Frankle, J.[Jonathan],
Stephenson, C.[Cory],
Kuleshov, V.[Volodymyr],
Common Canvas: Open Diffusion Models Trained on Creative-Commons Images,
CVPR24(8250-8260)
IEEE DOI
2410
Training, Computational modeling, Transfer learning, Text to image,
Diffusion models, Data models, diffusion, copyright, text2image,
dataset
BibRef
Mo, W.[Wenyi],
Zhang, T.Y.[Tian-Yu],
Bai, Y.[Yalong],
Su, B.[Bing],
Wen, J.R.[Ji-Rong],
Yang, Q.[Qing],
Dynamic Prompt Optimizing for Text-to-Image Generation,
CVPR24(26617-26626)
IEEE DOI
2410
Uniform resource locators, Training, Image synthesis, Semantics,
Refining, Text to image, Reinforcement learning,
Diffusion Model
BibRef
Zhang, G.[Gong],
Wang, K.[Kai],
Xu, X.Q.[Xing-Qian],
Wang, Z.Y.[Zhang-Yang],
Shi, H.[Humphrey],
Forget-Me-Not: Learning to Forget in Text-to-Image Diffusion Models,
WhatNext24(1755-1764)
IEEE DOI
2410
Adaptation models, Privacy, Accuracy, Computational modeling,
Knowledge based systems, Text to image, Safety, text-to-image,
concept forgetting
BibRef
Qi, T.H.[Tian-Hao],
Fang, S.C.[Shan-Cheng],
Wu, Y.Z.[Yan-Ze],
Xie, H.T.[Hong-Tao],
Liu, J.W.[Jia-Wei],
Chen, L.[Lang],
He, Q.[Qian],
Zhang, Y.D.[Yong-Dong],
DEADiff: An Efficient Stylization Diffusion Model with Disentangled
Representations,
CVPR24(8693-8702)
IEEE DOI Code:
WWW Link.
2410
Learning systems, Visualization, Semantics, Text to image,
Feature extraction, Diffusion models
BibRef
Patel, M.[Maitreya],
Kim, C.[Changhoon],
Cheng, S.[Sheng],
Baral, C.[Chitta],
Yang, Y.Z.[Ye-Zhou],
ECLIPSE: A Resource-Efficient Text-to-Image Prior for Image
Generations,
CVPR24(9069-9078)
IEEE DOI Code:
WWW Link.
2410
Training, Image coding, Image synthesis, Computational modeling,
Text to image, Contrastive learning, Diffusion models,
ECLIPSE
BibRef
Ramasinghe, S.[Sameera],
Shevchenko, V.[Violetta],
Avraham, G.[Gil],
Thalaiyasingam, A.[Ajanthan],
Accept the Modality Gap: An Exploration in the Hyperbolic Space,
CVPR24(27253-27262)
IEEE DOI
2410
Text to image, Machine learning, Linear programming,
multimodal learning, modality gap
BibRef
Li, C.[Cheng],
Qi, Y.[Yali],
Zeng, Q.T.[Qing-Tao],
Lu, L.[Likun],
Comparison of Image Generation methods based on Diffusion Models,
CVIDL23(1-4)
IEEE DOI
2403
Training, Deep learning, Learning systems, Image synthesis,
Computational modeling, Diffusion models
BibRef
Sehwag, V.[Vikash],
Hazirbas, C.[Caner],
Gordo, A.[Albert],
Ozgenel, F.[Firat],
Ferrer, C.C.[Cristian Canton],
Generating High Fidelity Data from Low-density Regions using
Diffusion Models,
CVPR22(11482-11491)
IEEE DOI
2210
Manifolds, Computational modeling, Diffusion processes,
Data models, Representation learning
BibRef
Chapter on 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing continues in
Diffusion for Layout Control in Text to Image Generation .