Awesome-Controllable-T2I-Diffusion-Models

A curated collection of research on controlling text-to-image diffusion models with novel conditions, including personalization, spatial control, and multimodal generation. Recent entries also cover control of flow-matching image models, preference-based personalization, and studies of controllability.

Our survey, Controllable Generation with Text-to-Image Diffusion Models: A Survey, is published in IEEE TPAMI, volume 48, issue 4, pages 4771–4791, April 2026.

Statistics count each paper once, including papers listed in multiple categories. Years use the first arXiv submission date, with the publication or announced conference year used for papers without an identified arXiv record. Paper-level data · Counts and methodology

💖 Citation

If you find value in our survey paper or curated collection, please consider citing our work and starring our repo to support us.

@article{cao2026controllable,
  title={Controllable Generation With Text-to-Image Diffusion Models: A Survey},
  author={Pu Cao and Feng Zhou and Qing Song and Lu Yang},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  volume={48},
  number={4},
  pages={4771--4791},
  year={2026},
  doi={10.1109/TPAMI.2025.3646548}
}

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Suggest a paper or a metadata correction through an issue. Include the following information so maintainers can verify and classify the entry:

1. Paper title
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🌈 Contents

• Generation with Specific Condition
  • Personalization
    • Subject-Driven Generation
    • Person-Driven Generation
    • Style-Driven Generation
    • Interaction-Driven Generation
    • Image-Driven Generation
    • Distribution-Driven Generation
    • Preference-Driven Generation
  • Spatial Control
  • Advanced Text-Conditioned Generation
  • In-Context Generation
  • Brain-Guided Generation
  • Sound-Guided Generation
  • Text Rendering
• Generation with Multiple Conditions
  • Joint Training
  • Continual Learning
  • Weight Fusion
  • Attention-based Integration
  • Guidance Composition
• Universal Controllable Generation
  • Universal Conditional Score Prediction
  • Universal Condition-Guided Score Estimation
• Analysis and Evaluation

🚀Generation with Specific Condition

🍇Personalization

🍉Subject-Driven Generation

MorphSIG: Subject-Driven Image Generation via Decoupled Anchoring and Feature Transport. Hailong Yan, Yongrui Zhang, Xiangtao Zhang, Le Zhang. NeurIPS 2026 (accepted). [Paper] [arXiv]

ReCoG: Relational Concept Graph for Training-Free Personalization. Changseon Yu, Hyeokjun Kweon. NeurIPS 2026 (accepted). [Paper] [arXiv]

Diffu-LoRA: A Novel Low-Rank Adaptation for Personalized Diffusion Models. Tianjing Li, Wei Zhu. arXiv 2026. [Paper]

Disentangling Dual Image References in Frequency Aware Diffusion Models for Personalized Generation. Haipeng Liu, Yang Wang, Meng Wang. NeurIPS 2026 (accepted). [Paper] [arXiv]

RefDiT: Local Attribute Guidance in Reference-Based Image Generation. Rameshwar Mishra, Srikrishna Karanam, A V Subramanyam. arXiv 2026. [Paper]

CRAFT: Constrained Reward via Attention Fine-Tuning for Subject Personalization without Composed Targets. Jihun Park, Kyoungmin Lee, Jongmin Gim, Hyeonseo Jo, Jaeyeul Kim, Han Zou, Zhenpeng Zhan, Yan Zhang, Sunghoon Im. arXiv 2026. [Paper]

In-Loop Model Adaptation with Coupled Latent-Noise Guidance for High-Fidelity Subject-Driven Text-to-Image Generation. Yushun Tang, Weiming Chen, Siyi Liu, Yi Zhang, Feng Wu, Zhihai He. arXiv 2026. [Paper]

TreeAdapter: Hierarchical Taxonomy-Guided Adapter Composition for Fine-Grained Species Image Generation. Yuze Sun, Zhongjie Duan, Yingda Chen. arXiv 2026. [Paper]

From Open Loop to Closed Loop: A Test-Time Iterative Optimization Framework for Reference-Consistent Image Generation. Baixuan Zhao, Xinyu Zhang, Huayu Zheng, Shuaicheng Liu, Xiongkuo Min, Guangtao Zhai, Xiaohong Liu. arXiv 2026. [Paper]

LILAC: Layer-Wise Independent LoRAs and Cascaded Conditioning for Multi-Concept Customization of Diffusion Models. Marian Lupascu, Sebastian Ripa, Mihai Trascau, Mariana-Iuliana Georgescu, Ionut Mironica. arXiv 2026. [Paper]

Decoupled Guidance: Disentangling Subject and Context Pathways in Text-to-Image Personalization. Seongmin Kim, Kyucheol Shin, Heesun Jung, Jinseo Kim, Sungyong Baik. arXiv 2026. [Paper]

HomeDiffusion: Zero-Shot Object Customization with Multi-View Representation Learning for Indoor Scenes. Guoqiu Li, Jin Song, Yiyun Fei. AAAI 2025. [Paper] [arXiv]

Keep The Essentials: Efficient Reference Conditioned Generation via Token Dropping. Rishubh Parihar, Ayush Raina, R. Venkatesh Babu, Or Patashnik. arXiv 2026. [Paper]

Redirecting the Flow: Image Customization through Attention Distribution Shift. Jie Li, Suorong Yang, Jian Zhao, Furao Shen. arXiv 2026. [Paper]

Equilibrated Diffusion: Frequency-aware Textual Embedding for Equilibrated Image Customization. Liyuan Ma, Xueji Fang, Guo-Jun Qi. ACM MM 2024. [Paper] [arXiv]

Squeezing Capacity from Multimodal Large Language Models for Subject-driven Generation. Shuhong Zheng, Aashish Kumar Misraa, Yu-Teng Li, Yu-Jhe Li, Igor Gilitschenski. arXiv 2026. [Paper]

SwiftPie: Lightning-fast Subject-driven Image Personalization via One step Diffusion. Huy Duong, Trong-Tung Nguyen, Cuong Pham, Anh Tran, Khoi Nguyen, Minh Hoai. arXiv 2026. [Paper]

SEAL: Semantic-aware Single-image Sticker Personalization with a Large-scale Sticker-tag Dataset. Changhyun Roh, Yonghyun Jeong, Jonghyun Lee, Chanho Eom, Jihyong Oh. arXiv 2026. [Paper]

Disentangling to Re-couple: Resolving the Similarity-Controllability Paradox in Subject-Driven Text-to-Image Generation. Shuang Li, Chao Deng, Hang Chen, Liqun Liu, Zhenyu Hu, Te Cao, Mengge Xue, Yuan Chen, Peng Shu, Huan Yu, Jie Jiang. CVPR 2026. [Paper] [arXiv]

Zero-Shot Personalization of Objects via Textual Inversion. Aniket Roy, Maitreya Suin, Rama Chellappa. arXiv 2026. [Paper]

Not All Layers Are Created Equal: Adaptive LoRA Ranks for Personalized Image Generation. Donald Shenaj, Federico Errica, Antonio Carta. arXiv 2026. [Paper]

Leveraging Cross-Modal Knowledge Transfer for Knowledge-Aware Concept Customization. Chenyang Zhu, Hongxiang Li, Xiu Li, Long Chen. ECCV 2026. [Paper] [arXiv]

PureCC: Pure Learning for Text-to-Image Concept Customization. Zhichao Liao, Xiaole Xian, Qingyu Li, Wenyu Qin, Meng Wang, Weicheng Xie, Siyang Song, Pingfa Feng, Long Zeng, Liang Pan. CVPR 2026. [Paper] [arXiv]

FlowFixer: Towards Detail-Preserving Subject-Driven Generation. Jinyoung Jun, Won-Dong Jang, Wenbin Ouyang, Raghudeep Gadde, Jungbeom Lee. CVPR 2026. [Paper] [arXiv]

ConceptPrism: Concept Disentanglement in Personalized Diffusion Models via Residual Token Optimization. Minseo Kim, Minchan Kwon, Dongyeun Lee, Yunho Jeon, Junmo Kim. CVPR 2026. [Paper] [arXiv]

Inject Where It Matters: Training-Free Spatially-Adaptive Identity Preservation for Text-to-Image Personalization. Guandong Li, Mengxia Ye. arXiv 2026. [Paper]

Unified Personalized Understanding, Generating and Editing. Yu Zhong, Tianwei Lin, Ruike Zhu, Yuqian Yuan, Haoyu Zheng, Liang Liang, Wenqiao Zhang, Feifei Shao, Haoyuan Li, Wanggui He, Hao Jiang, Yueting Zhuang. CVPR 2026. [Paper] [arXiv]

Unified Customized Generation by Disentangled Reward Modeling. Shaojin Wu, Mengqi Huang, Yufeng Cheng, Wenxu Wu, Jiahe Tian, Yiming Luo, Fei Ding, Qian He. CVPR 2026. [Paper]

Consis-GCPO: Consistency-Preserving Group Causal Preference Optimization for Vision Customization. Qiaoqiao Jin, Dong She, Siming Fu, Hualiang Wang, weihao zhou, Jidong Jiang. ICLR 2026. [Paper]

Boost the Identity-Preserving Embedding for Consistent Visual Generation. Zixun Xia, Kai Wang, Shuyu Guo, Boqian Li, Jian Yang, Yaxing Wang. ICML 2026. [Paper]

TOPA: Mitigating Concept Dominance in Diffusion Personalization via Target-Oriented Perturbation Augmentation. Jiayou Lu, Mingzhi Lyu, Junfeng Huang, Wai-Kin Adams Kong. ECCV 2026. [Paper]

Beyond Pixel Mimicry: Disentangled Self-Similarity Rewards for Diverse Subject-Driven Generation. Qian Wang, Zhenyu Li, Abdelrahman Eldesokey, Peter Wonka. ECCV 2026. [Paper]

Toward Semantically-Consistent Tuning-Free Customization for Rectified Flow Transformers. Jian Jin, Kai Zhang, Zhenyong Fu, Jian Yang. NeurIPS 2026 (accepted). [Paper]

WaveletLoRA: Frequency-Aware Content-Style Decomposition for Personalized Image Generation. Peiyao Wang, Jiahui Sun, Weining Wang, Jing Liu. NeurIPS 2026 (accepted). [Paper]

Identifying and Mitigating Diversity Collapse in Zero-Shot Personalization with I2I Editing Models. Uichan Lee, Jongeon Baek, Sangheum Hwang. NeurIPS 2026 (accepted). [Paper]

Where and When Identity Forms: Identity-Vital Attention Redistribution for Training-Free Subject-Driven Generation. Luan Thanh Trinh, Atsuki Osanai, Kenji Doi. NeurIPS 2026 (accepted). [Paper]

Continuous Personalized Diffusion Model via Spinor-Component Forward Geometry. GeonWoo Jeong, SEUNG HUN OH, Sang Beom Chu, WONJUN KIM, Bokyoon Na. NeurIPS 2026 (accepted). [Paper]

Mix-Opt: Mixed Optimization for Memory-Efficient Personalization of Text-to-Image Diffusion Models. Seokeon Choi, Sunghyun Park, Hyoungwoo Park, Jeongho Kim, Sungrack Yun. NeurIPS 2026 (accepted). [Paper]

Object Fusion via Diffusion Time-step for Customized Image Editing with Single Example. Xue Song, Zhongqi Yue, Jiequan Cui, Hanwang Zhang, Jingjing Chen. AAAI 2026. [Paper]

Dual Optimal Transport for Multi-Concept Composition: Structure Alignment and Texture Injection in Diffusion Models. Hao Fu, Tianyu Su, Meng Liu, Chenfang Yang, Tian Gan. ICML 2026. [Paper]

ASemConsist: Adaptive Semantic Feature Control for Training-Free Identity-Consistent Generation. Shin Seong Kim, Minjung Shin, Hyunin Cho, Youngjung Uh. arXiv 2025. [Paper]

Geometric Disentanglement of Text Embeddings for Subject-Consistent Text-to-Image Generation using A Single Prompt. Shangxun Li, Youngjung Uh. arXiv 2025. [Paper]

Directional Textual Inversion for Personalized Text-to-Image Generation. Kunhee Kim, NaHyeon Park, Kibeom Hong, Hyunjung Shim. ICLR 2026. [Paper] [arXiv]

Omni-Attribute: Open-vocabulary Attribute Encoder for Visual Concept Personalization. Tsai-Shien Chen, Aliaksandr Siarohin, Gordon Guocheng Qian, Kuan-Chieh Jackson Wang, Egor Nemchinov, Moayed Haji-Ali, Riza Alp Guler, Willi Menapace, Ivan Skorokhodov, Anil Kag, Jun-Yan Zhu, Sergey Tulyakov. CVPR 2026. [Paper] [arXiv]

Dynamic Image Prompt Adapter for Scalable Zero-shot Personalized Text-to-Image Generation. Zhizhong Wang, Tianyi Chu, Richard Wang, Nanyang Wang, Kehan Li. ECCV 2026. [Paper] [arXiv]

LoFA: Learning to Predict Personalized Prior for Fast Adaptation of Visual Generative Models. Yiming Hao, Mutian Xu, Chongjie Ye, Jie Qin, Shunlin Lu, Yipeng Qin, Xiaoguang Han. CVPR 2026. [Paper] [arXiv]

Not All Birds Look The Same: Identity-Preserving Generation For Birds. Aaron Sun, Oindrila Saha, Subhransu Maji. CVPR 2026. [Paper] [arXiv]

PhyCustom: Towards Realistic Physical Customization in Text-to-Image Generation. Fan Wu, Cheng Chen, Zhoujie Fu, Jiacheng Wei, Yi Xu, Deheng Ye, Guosheng Lin. arXiv 2025. [Paper]

MINDiff: Mask-Integrated Negative Attention for Controlling Overfitting in Text-to-Image Personalization. Seulgi Jeong, Jaeil Kim. arXiv 2025. [Paper]

Coffee: Controllable Diffusion Fine-tuning. Ziyao Zeng, Jingcheng Ni, Ruyi Liu, Alex Wong. arXiv 2025. [Paper]

FreeFuse: Multi-Subject LoRA Fusion via Adaptive Token-Level Routing at Test Time. Yaoli Liu, Yao-Xiang Ding, Kun Zhou. arXiv 2025. [Paper]

From Competition to Synergy: Unlocking Reinforcement Learning for Subject-Driven Image Generation. Ziwei Huang, Ying Shu, Hao Fang, Quanyu Long, Wenya Wang, Qiushi Guo, Tiezheng Ge, Leilei Gan. arXiv 2025. [Paper]

Chimera: Compositional Image Generation using Part-based Concepting. Shivam Singh, Yiming Chen, Agneet Chatterjee, Amit Raj, James Hays, Yezhou Yang, Chitta Baral. arXiv 2025. [Paper]

ConceptSplit: Decoupled Multi-Concept Personalization of Diffusion Models via Token-wise Adaptation and Attention Disentanglement. Habin Lim, Yeongseob Won, Juwon Seo, Gyeong-Moon Park. ICCV 2025. [Paper] [arXiv]

DEFT: Decompositional Efficient Fine-Tuning for Text-to-Image Models. Komal Kumar, Rao Anwer, Fahad Shahbaz Khan, Salman Khan, Ivan Laptev, Hisham Cholakkal. NeurIPS 2025. [Paper] [arXiv] [DOI]

CusEnhancer: A Zero-Shot Scene and Controllability Enhancement Method for Photo Customization via ResInversion. Maoye Ren, Praneetha Vaddamanu, Jianjin Xu, Fernando De la Torre Frade. arXiv 2025. [Paper]

One-shot Embroidery Customization via Contrastive LoRA Modulation. Jun Ma, Qian He, Gaofeng He, Huang Chen, Chen Liu, Xiaogang Jin, Huamin Wang. ACM TOG 2025. [Paper] [arXiv]

Stencil: Subject-Driven Generation with Context Guidance. Gordon Chen, Ziqi Huang, Cheston Tan, Ziwei Liu. arXiv 2025. [Paper]

Animalbooth: multimodal feature enhancement for animal subject personalization. Chen Liu, Haitao Wu, Kafeng Wang, Weiran Huang. arXiv 2025. [Paper]

TIDE: Achieving Balanced Subject-Driven Image Generation via Target-Instructed Diffusion Enhancement. Jibai Lin, Bo Ma, Yating Yang, Xi Zhou, Rong Ma, Turghun Osman, Ahtamjan Ahmat, Rui Dong, Lei Wang. arXiv 2025. [Paper]

Steering Guidance for Personalized Text-to-Image Diffusion Models. Sunghyun Park, Seokeon Choi, Hyoungwoo Park, Sungrack Yun. ICCV 2025. [Paper] [arXiv]

Zero-Shot Dynamic Concept Personalization with Grid-Based LoRA. Rameen Abdal, Or Patashnik, Ekaterina Deyneka, Hao Chen, Aliaksandr Siarohin, Sergey Tulyakov, Daniel Cohen-Or, Kfir Aberman. SIGGRAPH Asia 2025. [Paper] [arXiv]

FreeCus: Free Lunch Subject-driven Customization in Diffusion Transformers. Yanbing Zhang, Zhe Wang, Qin Zhou, Mengping Yang. ICCV 2025. [Paper] [arXiv]

ID-EA: Identity-driven Text Enhancement and Adaptation with Textual Inversion for Personalized Text-to-Image Generation. Hyun-Jun Jin, Young-Eun Kim, Seong-Whan Lee. arXiv 2025. [Paper]

CoDi: Subject-Consistent and Pose-Diverse Text-to-Image Generation. Zhanxin Gao, Beier Zhu, Liang Yao, Jian Yang, Ying Tai. ICLR 2026. [Paper] [Proceedings]

T-LoRA: Single Image Diffusion Model Customization Without Overfitting. Vera Soboleva, Aibek Alanov, Andrey Kuznetsov, Konstantin Sobolev. AAAI 2026. [Paper] [arXiv]

APT: Adaptive Personalized Training for Diffusion Models with Limited Data. JungWoo Chae, Jiyoon Kim, JaeWoong Choi, Kyungyul Kim, Sangheum Hwang. CVPR 2025. [Paper] [arXiv]

IC-Custom: Diverse Image Customization via In-Context Learning. Yaowei Li, Xiaoyu Li, Zhaoyang Zhang, Yuxuan Bian, Gan Liu, Xinyuan Li, Jiale Xu, Wenbo Hu, Yating Liu, Lingen Li, Jing Cai, Yuexian Zou, Yancheng He, Ying Shan. ICLR 2026. [Paper] [arXiv]

Mitigating Semantic Collapse in Generative Personalization with Test-Time Embedding Adjustment. Anh Bui, Thuy-Trang Vu, Trung Le, Junae Kim, Tamas Abraham, Rollin Omari, Amardeep Kaur, Dinh Phung. ICLR 2026. [Paper] [arXiv]

Preserve Anything: Controllable Image Synthesis with Object Preservation. Prasen Kumar Sharma, Neeraj Matiyali, Siddharth Srivastava, Gaurav Sharma. ICCV 2025. [Paper] [arXiv]

Noise Consistency Regularization for Improved Subject-Driven Image Synthesis. Yao Ni, Song Wen, Piotr Koniusz, Anoop Cherian. arXiv 2025. [Paper]

PartComposer: Learning and Composing Part-Level Concepts from Single-Image Examples. Junyu Liu, R. Kenny Jones, Daniel Ritchie. arXiv 2025. [Paper]

ComposeAnything: Composite Object Priors for Text-to-Image Generation. Zeeshan Khan, Shizhe Chen, Cordelia Schmid. arXiv 2025. [Paper]

AlignGen: Boosting Personalized Image Generation with Cross-Modality Prior Alignment. Yiheng Lin, Shifang Zhao, Ting Liu, Xiaochao Qu, Luoqi Liu, Yao Zhao, Yunchao Wei. arXiv 2025. [Paper]

Preserve and Personalize: Personalized Text-to-Image Diffusion Models without Distributional Drift. Gihoon Kim, Hyungjin Park, Taesup Kim. ICLR 2026. [Paper] [arXiv]

Mod-Adapter: Tuning-Free and Versatile Multi-concept Personalization via Modulation Adapter. Weizhi Zhong, Huan Yang, Zheng Liu, Huiguo He, Zijian He, Xuesong Niu, Di ZHANG, Guanbin Li. ICLR 2026. [Paper] [arXiv]

UniCTokens: Boosting Personalized Understanding and Generation via Unified Concept Tokens. Ruichuan An, Sihan Yang, Renrui Zhang, Zijun Shen, Ming Lu, Gaole Dai, Hao Liang, Ziyu Guo, Shilin Yan, Yulin Luo, Bocheng Zou, Chaoqun Yang, Wentao Zhang. NeurIPS 2025. [Paper] [arXiv] [DOI]

DRC: Enhancing Personalized Image Generation via Disentangled Representation Composition. Yiyan Xu, Wuqiang Zheng, Wenjie Wang, Fengbin Zhu, Xinting Hu, Yang Zhang, Fuli Feng, Tat-Seng Chua. ACM MM 2025. [Paper] [arXiv]

DreamO: A Unified Framework for Image Customization. Chong Mou, Yanze Wu, Wenxu Wu, Zinan Guo, Pengze Zhang, Yufeng Cheng, Yiming Luo, Fei Ding, Shiwen Zhang, Xinghui Li, Mengtian Li, Mingcong Liu, Yunsheng Jiang, Shaojin Wu, Songtao Zhao, Jian Zhang, Qian He, Xinglong Wu. SIGGRAPH Asia 2025. [Paper] [arXiv] [Code]

InstantCharacter: Personalize Any Characters with a Scalable Diffusion Transformer Framework. Jiale Tao, Yanbing Zhang, Qixun Wang, Yiji Cheng, Haofan Wang, Xu Bai, Zhengguang Zhou, Ruihuang Li, Linqing Wang, Chunyu Wang, Qin Lin, Qinglin Lu. arXiv 2025. [Paper] [Code]

Flux Already Knows -- Activating Subject-Driven Image Generation without Training. Hao Kang, Stathi Fotiadis, Liming Jiang, Qing Yan, Yumin Jia, Zichuan Liu, Min Jin Chong, Xin Lu. arXiv 2025. [Paper]

FlexIP: Dynamic Control of Preservation and Personality for Customized Image Generation. Linyan Huang, Haonan Lin, Yanning Zhou, Kaiwen Xiao. arXiv 2025. [Paper]

Less-to-More Generalization: Unlocking More Controllability by In-Context Generation. Shaojin Wu, Mengqi Huang, Wenxu Wu, Yufeng Cheng, Fei Ding, Qian He. ICCV 2025. [Paper] [Code] [Project]

Meta-LoRA: Meta-Learning LoRA Components for Domain-Aware ID Personalization. Barış Batuhan Topal, Umut Özyurt, Zafer Doğan Budak, Ramazan Gokberk Cinbis. arXiv 2025. [Paper]

Single Image Iterative Subject-driven Generation and Editing. Yair Shpitzer, Gal Chechik, Idan Schwartz. arXiv 2025. [Paper] [Code] [Project]

Efficient Personalization of Quantized Diffusion Model without Backpropagation. Hoigi Seo, Wongi Jeong, Kyungryeol Lee, Se Young Chun. CVPR 2025. [Paper] [arXiv]

Personalize Anything for Free with Diffusion Transformer. Haoran Feng, Zehuan Huang, Lin Li, Lu Sheng. AAAI 2026. [Paper] [arXiv] [Code] [Project]

Conceptrol: Concept Control of Zero-shot Personalized Image Generation. Qiyuan He, Angela Yao. arXiv 2025. [Paper]

ACCORD: Alleviating Concept Coupling through Dependence Regularization for Text-to-Image Diffusion Personalization. Shi Zhan Liu, Hao ZHENG, Hang Yu, Jianguo Li. ICLR 2026. [Paper] [arXiv]

SYNTHIA: Novel Concept Design with Affordance Composition. Hyeonjeong Ha, Xiaomeng Jin, Jeonghwan Kim, Jiateng Liu, Zhenhailong Wang, Khanh Duy Nguyen, Ansel Blume, Nanyun Peng, Kai-Wei Chang, Heng Ji. arXiv 2025. [Paper]

E-MD3C: Taming Masked Diffusion Transformers for Efficient Zero-Shot Object Customization. Trung X. Pham, Zhang Kang, Ji Woo Hong, Xuran Zheng, Chang D. Yoo. arXiv 2025. [Paper]

Generating Multi-Image Synthetic Data for Text-to-Image Customization. Nupur Kumari, Xi Yin, Jun-Yan Zhu, Ishan Misra, Samaneh Azadi. ICCV 2025. [Paper] [arXiv]

One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt. Tao Liu, Kai Wang, Senmao Li, Joost van de Weijer, Fahad Khan, Shiqi Yang, Yaxing Wang, Jian Yang, Ming-Ming Cheng. ICLR 2025. [Paper] [arXiv]

TokenVerse: Versatile Multi-concept Personalization in Token Modulation Space. Daniel Garibi, Shahar Yadin, Roni Paiss, Omer Tov, Shiran Zada, Ariel Ephrat, Tomer Michaeli, Inbar Mosseri, Tali Dekel. ACM TOG 2025. [Paper] [arXiv]

Transformed Low-rank Adaptation via Tensor Decomposition and Its Applications to Text-to-image Models. Zerui Tao, Yuhta Takida, Naoki Murata, Qibin Zhao, Yuki Mitsufuji. ICCV 2025. [Paper] [arXiv]

SceneBooth: Diffusion-based Framework for Subject-preserved Text-to-Image Generation. Shang Chai, Zihang Lin, Min Zhou, Xubin Li, Liansheng Zhuang, Houqiang Li. arXiv 2025. [Paper]

Nested Attention: Semantic-aware Attention Values for Concept Personalization. Or Patashnik, Rinon Gal, Daniil Ostashev, Sergey Tulyakov, Kfir Aberman, Daniel Cohen-Or. SIGGRAPH 2025. [Paper] [arXiv]

TFCustom: Customized Image Generation with Time-Aware Frequency Feature Guidance. Mushui Liu, Dong She, Jingxuan Pang, Qihan Huang, Jiacheng Ying, Wanggui He, Yuanlei Hou, Siming Fu. CVPR 2025. [Paper]

PS-Diffusion: Photorealistic Subject-Driven Image Editing with Disentangled Control and Attention. Weicheng Wang, Guoli Jia, Zhongqi Zhang, Liang Lin, Jufeng Yang. CVPR 2025. [Paper]

UniversalBooth: Model-Agnostic Personalized Text-to-Image Generation. Songhua Liu, Ruonan Yu, Xinchao Wang. ICCV 2025. [Paper]

QR-LoRA: Efficient and Disentangled Fine-tuning via QR Decomposition for Customized Generation. Jiahui Yang, Yongjia Ma, Donglin Di, Jianxun Cui, Hao Li, Wei Chen, Yan Xie, Xun Yang, Wangmeng Zuo. ICCV 2025. [Paper]

P3S-Diffusion:A Selective Subject-driven Generation Framework via Point Supervision. Junjie Hu, Shuyong Gao, Lingyi Hong, Qishan Wang, Yuzhou Zhao, Yan Wang, Wenqiang Zhang. arXiv 2024. [Paper]

DECOR:Decomposition and Projection of Text Embeddings for Text-to-Image Customization. Geonhui Jang, Jin-Hwa Kim, Yong-Hyun Park, Junho Kim, Gayoung Lee, Yonghyun Jeong. arXiv 2024. [Paper]

ObjectMate: A Recurrence Prior for Object Insertion and Subject-Driven Generation. Daniel Winter, Asaf Shul, Matan Cohen, Dana Berman, Yael Pritch, Alex Rav-Acha, Yedid Hoshen. ICCV 2025. [Paper] [arXiv]

PatchDPO: Patch-level DPO for Finetuning-free Personalized Image Generation. Qihan Huang, Long Chan, Jinlong Liu, Wanggui He, Hao Jiang, Mingli Song, Jie Song. CVPR 2025. [Paper] [arXiv]

LoRA Diffusion: Zero-Shot LoRA Synthesis for Diffusion Model Personalization. Ethan Smith, Rami Seid, Alberto Hojel, Paramita Mishra, Jianbo Wu. arXiv 2024. [Paper]

InstantSwap: Fast Customized Concept Swapping across Sharp Shape Differences. Chenyang Zhu, Kai Li, Yue Ma, Longxiang Tang, Chengyu Fang, Chubin Chen, Qifeng Chen, Xiu Li. ICLR 2025. [Paper] [arXiv]

DreamBlend: Advancing Personalized Fine-tuning of Text-to-Image Diffusion Models. Shwetha Ram, Tal Neiman, Qianli Feng, Andrew Stuart, Son Tran, Trishul Chilimbi. arXiv 2024. [Paper]

Diffusion Self-Distillation for Zero-Shot Customized Image Generation. Shengqu Cai, Eric Ryan Chan, Yunzhi Zhang, Leonidas Guibas, Jiajun Wu, Gordon Wetzstein. CVPR 2025. [Paper] [arXiv]

DreamCache: Finetuning-Free Lightweight Personalized Image Generation via Feature Caching. Emanuele Aiello, Umberto Michieli, Diego Valsesia, Mete Ozay, Enrico Magli. CVPR 2025. [Paper] [Code] [Project]

DreamMix: Decoupling Object Attributes for Enhanced Editability in Customized Image Inpainting. Yicheng Yang, Pengxiang Li, Lu Zhang, Liqian Ma, Ping Hu, Siyu Du, Yunzhi Zhuge, Xu Jia, Huchuan Lu. arXiv 2024. [Paper]

Large-Scale Text-to-Image Model with Inpainting is a Zero-Shot Subject-Driven Image Generator. Chaehun Shin, Jooyoung Choi, Heeseung Kim, Sungroh Yoon. CVPR 2025. [Paper] [arXiv]

Foundation Cures Personalization: Improving Personalized Models’ Prompt Consistency via Hidden Foundation Knowledge. Yiyang Cai, Zhengkai Jiang, Yulong Liu, Chunyang Jiang, Wei Xue, Yike Guo, Wenhan Luo. NeurIPS 2025. [Paper] [arXiv] [DOI]

Hollowed Net for On-Device Personalization of Text-to-Image Diffusion Models. Wonguk Cho, Seokeon Choi, Debasmit Das, Matthias Reisser, Taesup Kim, Sungrack Yun, Fatih Porikli. NeurIPS 2024. [Paper] [arXiv] [DOI]

MagicTailor: Component-Controllable Personalization in Text-to-Image Diffusion Models. Donghao Zhou, Jiancheng Huang, Jinbin Bai, Jiaze Wang, Hao Chen, Guangyong Chen, Xiaowei Hu, Pheng-Ann Heng. arXiv 2024. [Paper]

DreamSteerer: Enhancing Source Image Conditioned Editability using Personalized Diffusion Models. Zhengyang Yu, Zhaoyuan Yang, Jing Zhang. NeurIPS 2024. [Paper] [arXiv] [DOI]

DisEnvisioner: Disentangled and Enriched Visual Prompt for Customized Image Generation. Jing He, Haodong Li, Yongzhe Hu, Guibao Shen, Yingjie Cai, Weichao Qiu, Ying-Cong Chen. ICLR 2025. [Paper] [Proceedings]

Resolving Multi-Condition Confusion for Finetuning-Free Personalized Image Generation. Qihan Huang, Siming Fu, Jinlong Liu, Hao Jiang, Yipeng Yu, Jie Song. AAAI 2025. [Paper] [arXiv]

CustomContrast: A Multilevel Contrastive Perspective for Subject-Driven Text-to-Image Customization. Nan Chen, Mengqi Huang, Zhuowei Chen, Yang Zheng, Lei Zhang, Zhendong Mao. AAAI 2025. [Paper] [arXiv]

CoRe: Context-Regularized Text Embedding Learning for Text-to-Image Personalization. Feize Wu, Yun Pang, Junyi Zhang, Lianyu Pang, Jian Yin, Baoquan Zhao, Qing Li, Xudong Mao. AAAI 2025. [Paper] [arXiv]

Subject-driven Text-to-Image Generation via Preference-based Reinforcement Learning. Yanting Miao, William Loh, Suraj Kothawade, Pascal Poupart, Abdullah Rashwan, Yeqing Li. NeurIPS 2024. [Paper] [arXiv] [DOI]

PartCraft: Crafting Creative Objects by Parts. Kam Woh Ng, Xiatian Zhu, Yi-Zhe Song, Tao Xiang. ECCV 2024. [Paper]

CustAny: Customizing Anything from A Single Example. Lingjie Kong, Kai Wu, Chengming Xu, Xiaobin Hu, Wenhui Han, Jinlong Peng, Donghao Luo, Mengtian Li, Jiangning Zhang, Chengjie Wang, Yanwei Fu. CVPR 2025. [Paper] [arXiv]

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P+- Extended Textual Conditioning in Text-to-Image Generation.<br