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Facial images have extensive practical applications. Although the current large-scale text-image diffusion models exhibit strong generation capabilities, it is challenging to generate the desired facial images using only text prompt. Image…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Dawei Dai , Mingming Jia , Yinxiu Zhou , Hang Xing , Chenghang Li

Diffusion Handles is a novel approach to enabling 3D object edits on diffusion images. We accomplish these edits using existing pre-trained diffusion models, and 2D image depth estimation, without any fine-tuning or 3D object retrieval. The…

Computer Vision and Pattern Recognition · Computer Science 2023-12-08 Karran Pandey , Paul Guerrero , Matheus Gadelha , Yannick Hold-Geoffroy , Karan Singh , Niloy Mitra

Although diffusion-based techniques have shown remarkable success in image generation and editing tasks, their abuse can lead to severe negative social impacts. Recently, some works have been proposed to provide defense against the abuse of…

Computer Vision and Pattern Recognition · Computer Science 2025-03-10 Zheng Li , Liangbin Xie , Jiantao Zhou , Xintao Wang , Haiwei Wu , Jinyu Tian

Recently, text-to-image (T2I) editing has been greatly pushed forward by applying diffusion models. Despite the visual promise of the generated images, inconsistencies with the expected textual prompt remain prevalent. This paper aims to…

Computer Vision and Pattern Recognition · Computer Science 2024-09-20 Aoxue Li , Mingyang Yi , Zhenguo Li

Image editing technologies are tools used to transform, adjust, remove, or otherwise alter images. Recent research has significantly improved the capabilities of image editing tools, enabling the creation of photorealistic and semantically…

Computer Vision and Pattern Recognition · Computer Science 2024-12-06 Quang Nguyen , Truong Vu , Trong-Tung Nguyen , Yuxin Wen , Preston K Robinette , Taylor T Johnson , Tom Goldstein , Anh Tran , Khoi Nguyen

Generative models have enabled intuitive image creation and manipulation using natural language. In particular, diffusion models have recently shown remarkable results for natural image editing. In this work, we propose to apply diffusion…

Large-scale text-to-image models have demonstrated amazing ability to synthesize diverse and high-fidelity images. However, these models are often violated by several limitations. Firstly, they require the user to provide precise and…

Computer Vision and Pattern Recognition · Computer Science 2023-05-09 Yupei Lin , Sen Zhang , Xiaojun Yang , Xiao Wang , Yukai Shi

Subject-driven image inpainting has recently gained prominence in image editing with the rapid advancement of diffusion models. Beyond image guidance, recent studies have explored incorporating text guidance to achieve identity-preserved…

Computer Vision and Pattern Recognition · Computer Science 2025-09-25 Yicheng Yang , Pengxiang Li , Lu Zhang , Liqian Ma , Ping Hu , Siyu Du , Yunzhi Zhuge , Xu Jia , Huchuan Lu

Image generation and editing have seen a great deal of advancements with the rise of large-scale diffusion models that allow user control of different modalities such as text, mask, depth maps, etc. However, controlled editing of videos…

Computer Vision and Pattern Recognition · Computer Science 2024-06-04 AmirHossein Zamani , Amir G. Aghdam , Tiberiu Popa , Eugene Belilovsky

In this paper, we introduce a novel task called language-guided joint audio-visual editing. Given an audio and image pair of a sounding event, this task aims at generating new audio-visual content by editing the given sounding event…

Computer Vision and Pattern Recognition · Computer Science 2024-11-12 Susan Liang , Chao Huang , Yapeng Tian , Anurag Kumar , Chenliang Xu

Text-guided diffusion models have significantly advanced image editing, enabling highly realistic and local modifications based on textual prompts. While these developments expand creative possibilities, their malicious use poses…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Valentina Bazyleva , Nicolo Bonettini , Gaurav Bharaj

Editing natural images using textual descriptions in text-to-image diffusion models remains a significant challenge, particularly in achieving consistent generation and handling complex, non-rigid objects. Existing methods often struggle to…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Dinh-Khoi Vo , Thanh-Toan Do , Tam V. Nguyen , Minh-Triet Tran , Trung-Nghia Le

Recent virtual try-on approaches have advanced by finetuning pre-trained text-to-image diffusion models to leverage their powerful generative ability. However, the use of text prompts in virtual try-on remains underexplored. This paper…

Computer Vision and Pattern Recognition · Computer Science 2025-08-08 Jeongho Kim , Hoiyeong Jin , Sunghyun Park , Jaegul Choo

With deeper exploration of diffusion model, developments in the field of image generation have triggered a boom in image creation. As the quality of base-model generated images continues to improve, so does the demand for further…

Graphics · Computer Science 2025-04-21 Jia Wang , Jie Hu , Xiaoqi Ma , Hanghang Ma , Xiaoming Wei , Enhua Wu

Generative diffusion models have advanced image editing with high-quality results and intuitive interfaces such as prompts and semantic drawing. However, these interfaces lack precise control, and the associated methods typically specialize…

Diffusion models have been widely deployed in various image generation tasks, demonstrating an extraordinary connection between image and text modalities. Although prior studies have explored the vulnerability of diffusion models from the…

Machine Learning · Computer Science 2025-01-06 Dingcheng Yang , Yang Bai , Xiaojun Jia , Yang Liu , Xiaochun Cao , Wenjian Yu

Language has emerged as a natural interface for image editing. In this paper, we introduce a method for region-based image editing driven by textual prompts, without the need for user-provided masks or sketches. Specifically, our approach…

Computer Vision and Pattern Recognition · Computer Science 2024-04-04 Yuanze Lin , Yi-Wen Chen , Yi-Hsuan Tsai , Lu Jiang , Ming-Hsuan Yang

Recent advances in diffusion transformers have shown remarkable generalization in visual synthesis, yet most dense perception methods still rely on text-to-image (T2I) generators designed for stochastic generation. We revisit this paradigm…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Yiqing Shi , Yiren Song , Mike Zheng Shou

Blind face restoration aims to recover high-quality facial images from various unidentified sources of degradation, posing significant challenges due to the minimal information retrievable from the degraded images. Prior knowledge-based…

Computer Vision and Pattern Recognition · Computer Science 2024-12-31 Wanglong Lu , Jikai Wang , Tao Wang , Kaihao Zhang , Xianta Jiang , Hanli Zhao

Diffusion-based video editing have reached impressive quality and can transform either the global style, local structure, and attributes of given video inputs, following textual edit prompts. However, such solutions typically incur heavy…

Computer Vision and Pattern Recognition · Computer Science 2024-09-02 Kumara Kahatapitiya , Adil Karjauv , Davide Abati , Fatih Porikli , Yuki M. Asano , Amirhossein Habibian