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Diffusion models have demonstrated their ability to generate diverse and high-quality images, sparking considerable interest in their potential for real image editing applications. However, existing diffusion-based approaches for local…

Computer Vision and Pattern Recognition · Computer Science 2025-07-22 Wenjing Huang , Shikui Tu , Lei Xu

3D style transfer enables the creation of visually expressive 3D content, enriching the visual appearance of 3D scenes and objects. However, existing VGG- and CLIP-based methods struggle to model multi-view consistency within the model…

Computer Vision and Pattern Recognition · Computer Science 2026-01-28 Yitong Yang , Xuexin Liu , Yinglin Wang , Jing Wang , Hao Dou , Changshuo Wang , Shuting He

Diffusion probabilistic models have achieved enormous success in the field of image generation and manipulation. In this paper, we explore a novel paradigm of using the diffusion model and classifier guidance in the latent semantic space…

Computer Vision and Pattern Recognition · Computer Science 2023-05-25 Changhao Shi , Haomiao Ni , Kai Li , Shaobo Han , Mingfu Liang , Martin Renqiang Min

Although recent advances in visual generation have been remarkable, most existing architectures still depend on distinct encoders for images and text. This separation constrains diffusion models' ability to perform cross-modal reasoning and…

Computer Vision and Pattern Recognition · Computer Science 2025-10-15 Kevin Li , Manuel Brack , Sudeep Katakol , Hareesh Ravi , Ajinkya Kale

Despite their generative power, diffusion models struggle to maintain style consistency across images conditioned on the same style prompt, hindering their practical deployment in creative workflows. While several training-free methods…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Jiexuan Zhang , Yiheng Du , Qian Wang , Weiqi Li , Yu Gu , Jian Zhang

While diffusion models have shown exceptional capabilities in aesthetic image synthesis, they often struggle with complex spatial understanding and reasoning. Existing approaches resort to Multimodal Large Language Models (MLLMs) to enhance…

Computer Vision and Pattern Recognition · Computer Science 2026-02-13 Wei Chen , Yancheng Long , Mingqiao Liu , Haojie Ding , Yankai Yang , Hongyang Wei , Yi-Fan Zhang , Bin Wen , Fan Yang , Tingting Gao , Han Li , Long Chen

By decomposing the image formation process into a sequential application of denoising autoencoders, diffusion models (DMs) achieve state-of-the-art synthesis results on image data and beyond. Additionally, their formulation allows for a…

Computer Vision and Pattern Recognition · Computer Science 2022-04-14 Robin Rombach , Andreas Blattmann , Dominik Lorenz , Patrick Esser , Björn Ommer

Recent advances in vision-language pre-training have enabled machines to perform better in multimodal object discrimination (e.g., image-text semantic alignment) and image synthesis (e.g., text-to-image generation). On the other hand,…

Computer Vision and Pattern Recognition · Computer Science 2023-06-02 Xiao Dong , Runhui Huang , Xiaoyong Wei , Zequn Jie , Jianxing Yu , Jian Yin , Xiaodan Liang

Fashion design is a complex creative process that blends visual and textual expressions. Designers convey ideas through sketches, which define spatial structure and design elements, and textual descriptions, capturing material, texture, and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-05 Federico Girella , Davide Talon , Ziyue Liu , Zanxi Ruan , Yiming Wang , Marco Cristani

In the accelerating era of human-instructed visual content creation, diffusion models have demonstrated remarkable generative potential. Yet their deployment is constrained by a dual bottleneck: semantic ambiguity in diverse prompts and the…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Jie Qin , Jie Wu , Weifeng Chen , Yueming Lyu

Unsupervised visual object tracking is a challenging task that requires following arbitrary targets in videos without training on ground-truth annotations. Despite considerable progress, existing state-of-the-art unsupervised trackers often…

Computer Vision and Pattern Recognition · Computer Science 2026-05-27 Zhengbo Zhang , Zhigang Tu , Junsong Yuan , De Wen Soh , Bo Du

Despite the success of generating high-quality images given any text prompts by diffusion-based generative models, prior works directly generate the entire images, but cannot provide object-wise manipulation capability. To support wider…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Runhui Huang , Kaixin Cai , Jianhua Han , Xiaodan Liang , Renjing Pei , Guansong Lu , Songcen Xu , Wei Zhang , Hang Xu

Image completion is a challenging task, particularly when ensuring that generated content seamlessly integrates with existing parts of an image. While recent diffusion models have shown promise, they often struggle with maintaining…

Computer Vision and Pattern Recognition · Computer Science 2025-04-22 Pourya Shamsolmoali , Masoumeh Zareapoor , Huiyu Zhou , Michael Felsberg , Dacheng Tao , Xuelong Li

Reconstructing 3D clothed humans from monocular images and videos is a fundamental problem with applications in virtual try-on, avatar creation, and mixed reality. Despite significant progress in human body recovery, accurately…

Computer Vision and Pattern Recognition · Computer Science 2026-03-02 Yingxuan You , Ren Li , Corentin Dumery , Cong Cao , Hao Li , Pascal Fua

Referring remote sensing image segmentation (RRSIS) enables the precise delineation of regions within remote sensing imagery through natural language descriptions, serving critical applications in disaster response, urban development, and…

Computer Vision and Pattern Recognition · Computer Science 2025-06-25 Zhe Dong , Yuzhe Sun , Tianzhu Liu , Yanfeng Gu

Recent successes in image synthesis are powered by large-scale diffusion models. However, most methods are currently limited to either text- or image-conditioned generation for synthesizing an entire image, texture transfer or inserting…

Computer Vision and Pattern Recognition · Computer Science 2023-05-23 Yufei Ye , Xueting Li , Abhinav Gupta , Shalini De Mello , Stan Birchfield , Jiaming Song , Shubham Tulsiani , Sifei Liu

Previously, non-autoregressive models were widely perceived as being superior in generation efficiency but inferior in generation quality due to the difficulties of modeling multiple target modalities. To enhance the multi-modality modeling…

Computation and Language · Computer Science 2023-11-30 Lihua Qian , Mingxuan Wang , Yang Liu , Hao Zhou

Existing makeup techniques often require designing multiple models to handle different inputs and align features across domains for different makeup tasks, e.g., beauty filter, makeup transfer, and makeup removal, leading to increased…

Computer Vision and Pattern Recognition · Computer Science 2025-07-04 Bo-Kai Ruan , Hong-Han Shuai

The body movements accompanying speech aid speakers in expressing their ideas. Co-speech motion generation is one of the important approaches for synthesizing realistic avatars. Due to the intricate correspondence between speech and motion,…

Multimedia · Computer Science 2024-08-28 Sen Wang , Jiangning Zhang , Xin Tan , Zhifeng Xie , Chengjie Wang , Lizhuang Ma

We propose a diffusion model-based approach, FloAtControlNet to generate cinemagraphs composed of animations of human clothing. We focus on human clothing like dresses, skirts and pants. The input to our model is a text prompt depicting the…

Computer Vision and Pattern Recognition · Computer Science 2024-11-25 Swasti Shreya Mishra , Kuldeep Kulkarni , Duygu Ceylan , Balaji Vasan Srinivasan