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Controllable text-to-image (T2I) diffusion models generate images conditioned on both text prompts and semantic inputs of other modalities like edge maps. Nevertheless, current controllable T2I methods commonly face challenges related to…

Computer Vision and Pattern Recognition · Computer Science 2024-05-24 Xuehai He , Jian Zheng , Jacob Zhiyuan Fang , Robinson Piramuthu , Mohit Bansal , Vicente Ordonez , Gunnar A Sigurdsson , Nanyun Peng , Xin Eric Wang

Diffusion Transformers (DiTs) have demonstrated exceptional capabilities in text-to-image synthesis. However, in the domain of controllable text-to-image generation using DiTs, most existing methods still rely on the ControlNet paradigm…

Computer Vision and Pattern Recognition · Computer Science 2025-08-15 Shanyuan Liu , Jian Zhu , Junda Lu , Yue Gong , Liuzhuozheng Li , Bo Cheng , Yuhang Ma , Liebucha Wu , Xiaoyu Wu , Dawei Leng , Yuhui Yin

Deep learning-based sketch-to-clothing image generation provides the initial designs and inspiration in the fashion design processes. However, clothing generation from freehand drawing is challenging due to the sparse and ambiguous…

Computer Vision and Pattern Recognition · Computer Science 2024-05-09 Yongming Zhang , Tianyu Zhang , Haoran Xie

Achieving machine autonomy and human control often represent divergent objectives in the design of interactive AI systems. Visual generative foundation models such as Stable Diffusion show promise in navigating these goals, especially when…

Computer Vision and Pattern Recognition · Computer Science 2023-11-03 Can Qin , Shu Zhang , Ning Yu , Yihao Feng , Xinyi Yang , Yingbo Zhou , Huan Wang , Juan Carlos Niebles , Caiming Xiong , Silvio Savarese , Stefano Ermon , Yun Fu , Ran Xu

With the wide application of diffusion model, the high cost of inference resources has became an important bottleneck for its universal application. Controllable generation, such as ControlNet, is one of the key research directions of…

Computer Vision and Pattern Recognition · Computer Science 2024-08-20 Zhaoli Deng , Kaibin Zhou , Fanyi Wang , Zhenpeng Mi

Text-to-Image diffusion models have made tremendous progress over the past two years, enabling the generation of highly realistic images based on open-domain text descriptions. However, despite their success, text descriptions often…

Computer Vision and Pattern Recognition · Computer Science 2023-10-31 Shihao Zhao , Dongdong Chen , Yen-Chun Chen , Jianmin Bao , Shaozhe Hao , Lu Yuan , Kwan-Yee K. Wong

Following the advancements in text-guided image generation technology exemplified by Stable Diffusion, video generation is gaining increased attention in the academic community. However, relying solely on text guidance for video generation…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Cong Wang , Jiaxi Gu , Panwen Hu , Haoyu Zhao , Yuanfan Guo , Jianhua Han , Hang Xu , Xiaodan Liang

Recent advances in conditional image generation from diffusion models have shown great potential in achieving impressive image quality while preserving the constraints introduced by the user. In particular, ControlNet enables precise…

Computer Vision and Pattern Recognition · Computer Science 2025-03-13 Hannah Kniesel , Pedro Hermosilla , Timo Ropinski

Diffusion models have demonstrated remarkable and robust abilities in both image and video generation. To achieve greater control over generated results, researchers introduce additional architectures, such as ControlNet, Adapters and…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Bohao Peng , Jian Wang , Yuechen Zhang , Wenbo Li , Ming-Chang Yang , Jiaya Jia

This paper introduces a generative model designed for multimodal control over text-to-image foundation generative AI models such as Stable Diffusion, specifically tailored for engineering design synthesis. Our model proposes parametric,…

Artificial Intelligence · Computer Science 2024-12-09 Rui Zhou , Yanxia Zhang , Chenyang Yuan , Frank Permenter , Nikos Arechiga , Matt Klenk , Faez Ahmed

Visual text generation has significantly advanced through diffusion models aimed at producing images with readable and realistic text. Recent works primarily use a ControlNet-based framework, employing standard font text images to control…

Computer Vision and Pattern Recognition · Computer Science 2024-07-23 Boqiang Zhang , Zuan Gao , Yadong Qu , Hongtao Xie

End-to-end backpropagation requires storing activations throughout all layers, creating memory bottlenecks that limit model scalability. Existing block-wise training methods offer means to alleviate this problem, but they rely on ad-hoc…

Machine Learning · Computer Science 2026-02-19 Makoto Shing , Masanori Koyama , Takuya Akiba

Controlling the spatial and semantic structure of diffusion-generated images remains a challenge. Existing methods like ControlNet rely on handcrafted condition maps and retraining, limiting flexibility and generalization. Inversion-based…

Computer Vision and Pattern Recognition · Computer Science 2025-11-10 Jiang Lin , Xinyu Chen , Song Wu , Zhiqiu Zhang , Jizhi Zhang , Ye Wang , Qiang Tang , Qian Wang , Jian Yang , Zili Yi

Recent approaches such as ControlNet offer users fine-grained spatial control over text-to-image (T2I) diffusion models. However, auxiliary modules have to be trained for each type of spatial condition, model architecture, and checkpoint,…

Computer Vision and Pattern Recognition · Computer Science 2023-12-13 Sicheng Mo , Fangzhou Mu , Kuan Heng Lin , Yanli Liu , Bochen Guan , Yin Li , Bolei Zhou

Recently, diffusion models like StableDiffusion have achieved impressive image generation results. However, the generation process of such diffusion models is uncontrollable, which makes it hard to generate videos with continuous and…

Computer Vision and Pattern Recognition · Computer Science 2023-08-04 Zhihao Hu , Dong Xu

Diffusion models have advanced from text-to-image (T2I) to image-to-image (I2I) generation by incorporating structured inputs such as depth maps, enabling fine-grained spatial control. However, existing methods either train separate models…

Computer Vision and Pattern Recognition · Computer Science 2025-08-01 Yucheng Xie , Fu Feng , Ruixiao Shi , Jing Wang , Yong Rui , Xin Geng

Text-to-music generation models are now capable of generating high-quality music audio in broad styles. However, text control is primarily suitable for the manipulation of global musical attributes like genre, mood, and tempo, and is less…

Sound · Computer Science 2023-11-14 Shih-Lun Wu , Chris Donahue , Shinji Watanabe , Nicholas J. Bryan

The Diffusion Transformer plays a pivotal role in advancing text-to-image and text-to-video generation, owing primarily to its inherent scalability. However, existing controlled diffusion transformer methods incur significant parameter and…

Computer Vision and Pattern Recognition · Computer Science 2026-02-27 Ke Cao , Jing Wang , Ao Ma , Jiasong Feng , Xuanhua He , Run Ling , Haowei Liu , Jian Lu , Wei Feng , Haozhe Wang , Hongjuan Pei , Yihua Shao , Zhanjie Zhang , Jie Zhang

Recently, there is a growing interest in creating computer-aided design (CAD) models based on user intent, known as controllable CAD generation. Existing work offers limited controllability and needs separate models for different types of…

Computer Vision and Pattern Recognition · Computer Science 2025-02-18 Zhanwei Zhang , Shizhao Sun , Wenxiao Wang , Deng Cai , Jiang Bian

The field of image synthesis has made tremendous strides forward in the last years. Besides defining the desired output image with text-prompts, an intuitive approach is to additionally use spatial guidance in form of an image, such as a…

Computer Vision and Pattern Recognition · Computer Science 2024-08-13 Denis Zavadski , Johann-Friedrich Feiden , Carsten Rother
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