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Related papers: EditScribe: Non-Visual Image Editing with Natural …

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This paper presents a novel method to manipulate the visual appearance (pose and attribute) of a person image according to natural language descriptions. Our method can be boiled down to two stages: 1) text guided pose generation and 2)…

Computer Vision and Pattern Recognition · Computer Science 2019-04-11 Xingran Zhou , Siyu Huang , Bin Li , Yingming Li , Jiachen Li , Zhongfei Zhang

Image processing holds immense potential for societal benefit, yet its full potential is often accessible only to tech-savvy experts. Bridging this knowledge gap and providing accessible tools for users of all backgrounds remains an…

Computer Vision and Pattern Recognition · Computer Science 2024-01-09 Sahan Dissanayaka , Oshan Mudanayaka , Thilina Halloluwa , Chameera De Silva

Given the steep learning curve of professional 3D software and the time-consuming process of managing large 3D assets, language-guided 3D scene editing has significant potential in fields such as virtual reality, augmented reality, and…

In a recorded situation, textual information is crucial for scene interpretation and decision making. The ability to edit text directly on images has a number of advantages, including error correction, text restoration, and image…

Computer Vision and Pattern Recognition · Computer Science 2021-12-01 Yujie Zhang

Contrastive language-image pre-training (CLIP) models have demonstrated considerable success across various vision-language tasks, such as text-to-image retrieval, where the model is required to effectively process natural language input to…

Computer Vision and Pattern Recognition · Computer Science 2024-02-26 Hyunjae Kim , Seunghyun Yoon , Trung Bui , Handong Zhao , Quan Tran , Franck Dernoncourt , Jaewoo Kang

Editing complex visual content from ambiguous or partially specified instructions remains a core challenge in vision-language modeling. Existing models can contextualize content but often fail to infer the underlying intent within a…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Umar Khalid , Kashif Munir , Hasan Iqbal , Azib Farooq , Jing Hua , Nazanin Rahnavard , Chen Chen , Victor Zhu , Zhengping Ji

A variety of text-guided image editing models have been proposed recently. However, there is no widely-accepted standard evaluation method mainly due to the subjective nature of the task, letting researchers rely on manual user study. To…

Computer Vision and Pattern Recognition · Computer Science 2025-05-02 Suho Ryu , Kihyun Kim , Eugene Baek , Dongsoo Shin , Joonseok Lee

Image editing serves as a practical yet challenging task considering the diverse demands from users, where one of the hardest parts is to precisely describe how the edited image should look like. In this work, we present a new form of…

Computer Vision and Pattern Recognition · Computer Science 2024-06-12 Xi Chen , Yutong Feng , Mengting Chen , Yiyang Wang , Shilong Zhang , Yu Liu , Yujun Shen , Hengshuang Zhao

Model editing aims to correct errors in large, pretrained models without altering unrelated behaviors. While some recent works have edited vision-language models (VLMs), no existing editors tackle reasoning-heavy tasks, which typically…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Jiaxing Qiu , Kaihua Hou , Roxana Daneshjou , Ahmed Alaa , Thomas Hartvigsen

Dense temporal annotation of procedural activity videos is vital for action understanding and embodied intelligence but remains labor-intensive due to reactive tools. Each correction is treated as an isolated edit, limiting reuse of…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Qian Yin , Di Wen , Kunyu Peng , David Schneider , Zeyun Zhong , Alexander Jaus , Zdravko Marinov , Jiale Wei , Ruiping Liu , Junwei Zheng , Yufan Chen , Chen Zhang , Lei Qi , Rainer Stiefelhagen

ChatGPT is attracting a cross-field interest as it provides a language interface with remarkable conversational competency and reasoning capabilities across many domains. However, since ChatGPT is trained with languages, it is currently not…

Computer Vision and Pattern Recognition · Computer Science 2023-03-09 Chenfei Wu , Shengming Yin , Weizhen Qi , Xiaodong Wang , Zecheng Tang , Nan Duan

Video is a powerful medium for communication and storytelling, yet reauthoring existing footage remains challenging. Even simple edits often demand expertise, time, and careful planning, constraining how creators envision and shape their…

Human-Computer Interaction · Computer Science 2026-04-07 Sitong Wang , Anh Truong , Lydia B. Chilton , Dingzeyu Li

Recent large-scale text-driven synthesis models have attracted much attention thanks to their remarkable capabilities of generating highly diverse images that follow given text prompts. Such text-based synthesis methods are particularly…

Computer Vision and Pattern Recognition · Computer Science 2022-08-03 Amir Hertz , Ron Mokady , Jay Tenenbaum , Kfir Aberman , Yael Pritch , Daniel Cohen-Or

Automatic image editing has great demands because of its numerous applications, and the use of natural language instructions is essential to achieving flexible and intuitive editing as the user imagines. A pioneering work in text-driven…

Computer Vision and Pattern Recognition · Computer Science 2023-04-04 Tsuyoshi Baba , Kosuke Nishida , Kyosuke Nishida

We present a training-free framework for continuous and controllable image editing at test time for text-conditioned generative models. In contrast to prior approaches that rely on additional training or manual user intervention, we find…

Computer Vision and Pattern Recognition · Computer Science 2026-03-19 Yigit Ekin , Yossi Gandelsman

Incorporating human feedback has been shown to be crucial to align text generated by large language models to human preferences. We hypothesize that state-of-the-art instructional image editing models, where outputs are generated based on…

Computer Vision and Pattern Recognition · Computer Science 2024-03-28 Shu Zhang , Xinyi Yang , Yihao Feng , Can Qin , Chia-Chih Chen , Ning Yu , Zeyuan Chen , Huan Wang , Silvio Savarese , Stefano Ermon , Caiming Xiong , Ran Xu

Instruction-based image editing (IIE) has advanced rapidly with the success of diffusion models. However, existing efforts primarily focus on simple and explicit instructions to execute editing operations such as adding, deleting, moving,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-14 Qingdong He , Xueqin Chen , Chaoyi Wang , Yanjie Pan , Xiaobin Hu , Zhenye Gan , Yabiao Wang , Chengjie Wang , Xiangtai Li , Jiangning Zhang

We present a novel system for sketch-based face image editing, enabling users to edit images intuitively by sketching a few strokes on a region of interest. Our interface features tools to express a desired image manipulation by providing…

Computer Vision and Pattern Recognition · Computer Science 2018-06-08 Tiziano Portenier , Qiyang Hu , Attila Szabó , Siavash Arjomand Bigdeli , Paolo Favaro , Matthias Zwicker

Instruction-guided image editing offers an intuitive way for users to edit images with natural language. However, diffusion-based editing models often struggle to accurately interpret complex user instructions, especially those involving…

Computer Vision and Pattern Recognition · Computer Science 2026-02-26 Ziyun Zeng , Hang Hua , Jiebo Luo

Precise and flexible image editing remains a fundamental challenge in computer vision. Based on the modified areas, most editing methods can be divided into two main types: global editing and local editing. In this paper, we choose the two…

Computer Vision and Pattern Recognition · Computer Science 2025-02-27 Ziqi Jiang , Zhen Wang , Long Chen
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