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Text-guided diffusion models have revolutionized image generation and editing, offering exceptional realism and diversity. Specifically, in the context of diffusion-based editing, where a source image is edited according to a target prompt,…

Computer Vision and Pattern Recognition · Computer Science 2023-10-20 Xuan Ju , Ailing Zeng , Yuxuan Bian , Shaoteng Liu , Qiang Xu

Object manipulation in images aims to not only edit the object's presentation but also gift objects with motion. Previous methods encountered challenges in concurrently handling static editing and dynamic generation, while also struggling…

Computer Vision and Pattern Recognition · Computer Science 2025-01-23 Ruisi Zhao , Zechuan Zhang , Zongxin Yang , Yi Yang

Recent advances in diffusion models have successfully enabled text-guided image inpainting. While it seems straightforward to extend such editing capability into the video domain, there have been fewer works regarding text-guided video…

Computer Vision and Pattern Recognition · Computer Science 2024-04-02 Zhixing Zhang , Bichen Wu , Xiaoyan Wang , Yaqiao Luo , Luxin Zhang , Yinan Zhao , Peter Vajda , Dimitris Metaxas , Licheng Yu

Recent advancements in personalizing text-to-image (T2I) diffusion models have shown the capability to generate images based on personalized visual concepts using a limited number of user-provided examples. However, these models often…

Computer Vision and Pattern Recognition · Computer Science 2024-02-20 Yan Hong , Jianfu Zhang

Large-scale diffusion models have achieved state-of-the-art results on text-to-image synthesis (T2I) tasks. Despite their ability to generate high-quality yet creative images, we observe that attribution-binding and compositional…

Computer Vision and Pattern Recognition · Computer Science 2023-03-02 Weixi Feng , Xuehai He , Tsu-Jui Fu , Varun Jampani , Arjun Akula , Pradyumna Narayana , Sugato Basu , Xin Eric Wang , William Yang Wang

Text-to-image (T2I) generative models achieve impressive visual fidelity but inherit and amplify demographic imbalances and cultural biases embedded in training data. We introduce T2I-BiasBench, a unified evaluation framework of thirteen…

Computer Vision and Pattern Recognition · Computer Science 2026-04-15 Nihal Jaiswal , Siddhartha Arjaria , Gyanendra Chaubey , Ankush Kumar , Aditya Singh , Anchal Chaurasiya

Text-to-image generation has witnessed great progress, especially with the recent advancements in diffusion models. Since texts cannot provide detailed conditions like object appearance, reference images are usually leveraged for the…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Zhiqi Huang , Huixin Xiong , Haoyu Wang , Longguang Wang , Zhiheng Li

This paper introduces LeftRefill, an innovative approach to efficiently harness large Text-to-Image (T2I) diffusion models for reference-guided image synthesis. As the name implies, LeftRefill horizontally stitches reference and target…

Computer Vision and Pattern Recognition · Computer Science 2024-03-05 Chenjie Cao , Yunuo Cai , Qiaole Dong , Yikai Wang , Yanwei Fu

Image editing approaches have become more powerful and flexible with the advent of powerful text-conditioned generative models. However, placing objects in an environment with a precise location and orientation still remains a challenge, as…

Computer Vision and Pattern Recognition · Computer Science 2025-06-27 Mohamed Omran , Dimitris Kalatzis , Jens Petersen , Amirhossein Habibian , Auke Wiggers

Personalized text-to-image (T2I) synthesis based on diffusion models has attracted significant attention in recent research. However, existing methods primarily concentrate on customizing subjects or styles, neglecting the exploration of…

Computer Vision and Pattern Recognition · Computer Science 2023-11-09 Hai Wang , Xiaoyu Xiang , Yuchen Fan , Jing-Hao Xue

Text-to-image models are showcasing the impressive ability to create high-quality and diverse generative images. Nevertheless, the transition from freehand sketches to complex scene images remains challenging using diffusion models. In this…

Computer Vision and Pattern Recognition · Computer Science 2024-07-10 Tianyu Zhang , Xiaoxuan Xie , Xusheng Du , Haoran Xie

Text-guided image editing has recently experienced rapid development. However, simultaneously performing multiple editing actions on a single image, such as background replacement and specific subject attribute changes, while maintaining…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Pengzhi Li , QInxuan Huang , Yikang Ding , Zhiheng Li

Since the advent of GANs and VAEs, image generation models have continuously evolved, opening up various real-world applications with the introduction of Stable Diffusion and DALL-E models. These text-to-image models can generate…

Computer Vision and Pattern Recognition · Computer Science 2024-09-25 Hyunwoo Yoo

Text-to-image diffusion models have emerged as powerful tools for high-quality image generation and editing. Many existing approaches rely on text prompts as editing guidance. However, these methods are constrained by the need for manual…

Computer Vision and Pattern Recognition · Computer Science 2025-05-21 Yuanyuan Chang , Yinghua Yao , Tao Qin , Mengmeng Wang , Ivor Tsang , Guang Dai

Large-scale Text-to-Image (T2I) diffusion models demonstrate significant generation capabilities based on textual prompts. Based on the T2I diffusion models, text-guided image editing research aims to empower users to manipulate generated…

Computer Vision and Pattern Recognition · Computer Science 2024-05-03 Chuanming Tang , Kai Wang , Fei Yang , Joost van de Weijer

The advancement of diffusion models has pushed the boundary of text-to-3D object generation. While it is straightforward to composite objects into a scene with reasonable geometry, it is nontrivial to texture such a scene perfectly due to…

Computer Vision and Pattern Recognition · Computer Science 2024-06-05 Qi Wang , Ruijie Lu , Xudong Xu , Jingbo Wang , Michael Yu Wang , Bo Dai , Gang Zeng , Dan Xu

Text-conditioned image generation has made significant progress in recent years with generative adversarial networks and more recently, diffusion models. While diffusion models conditioned on text prompts have produced impressive and…

Computer Vision and Pattern Recognition · Computer Science 2023-05-01 Azade Farshad , Yousef Yeganeh , Yu Chi , Chengzhi Shen , Björn Ommer , Nassir Navab

This paper investigates the problem of the current HOI detection methods and introduces DiffHOI, a novel HOI detection scheme grounded on a pre-trained text-image diffusion model, which enhances the detector's performance via improved data…

Computer Vision and Pattern Recognition · Computer Science 2023-05-23 Jie Yang , Bingliang Li , Fengyu Yang , Ailing Zeng , Lei Zhang , Ruimao Zhang

With the advance of text-to-image (T2I) diffusion models (e.g., Stable Diffusion) and corresponding personalization techniques such as DreamBooth and LoRA, everyone can manifest their imagination into high-quality images at an affordable…

Computer Vision and Pattern Recognition · Computer Science 2024-02-09 Yuwei Guo , Ceyuan Yang , Anyi Rao , Zhengyang Liang , Yaohui Wang , Yu Qiao , Maneesh Agrawala , Dahua Lin , Bo Dai

Natural language offers a highly intuitive interface for image editing. In this paper, we introduce the first solution for performing local (region-based) edits in generic natural images, based on a natural language description along with…

Computer Vision and Pattern Recognition · Computer Science 2023-03-22 Omri Avrahami , Dani Lischinski , Ohad Fried