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Related papers: Free-Editor: Zero-shot Text-driven 3D Scene Editin…

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Text-guided image editing has advanced rapidly with the rise of diffusion models. While flow-based inversion-free methods offer high efficiency by avoiding latent inversion, they often fail to effectively integrate source information,…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Kaixiang Yang , Boyang Shen , Xin Li , Yuchen Dai , Yuxuan Luo , Yueran Ma , Wei Fang , Qiang Li , Zhiwei Wang

Recent advances in training-free attention control methods have enabled flexible and efficient text-guided editing capabilities for existing generation models. However, current approaches struggle to simultaneously deliver strong editing…

Computer Vision and Pattern Recognition · Computer Science 2025-10-21 Zixin Yin , Ling-Hao Chen , Lionel Ni , Xili Dai

Concept erasure in Text-To-Image (T2I) diffusion models is vital for safe content generation, but existing inference-time methods face significant limitations. Feature-correction approaches often cause uncontrolled over-correction, while…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Qinghui Gong

We propose a high-quality 3D-to-3D conversion method, Instruct 3D-to-3D. Our method is designed for a novel task, which is to convert a given 3D scene to another scene according to text instructions. Instruct 3D-to-3D applies pretrained…

Computer Vision and Pattern Recognition · Computer Science 2023-03-29 Hiromichi Kamata , Yuiko Sakuma , Akio Hayakawa , Masato Ishii , Takuya Narihira

Large-scale text-to-image (T2I) diffusion models excel at open-domain synthesis but still struggle with precise text rendering, especially for multi-line layouts, dense typography, and long-tailed scripts such as Chinese. Prior solutions…

Computer Vision and Pattern Recognition · Computer Science 2026-01-05 Ruiqiang Zhang , Hengyi Wang , Chang Liu , Guanjie Wang , Zehua Ma , Weiming Zhang

Diffusion-based models, widely used in text-to-image generation, have proven effective in 2D representation learning. Recently, this framework has been extended to 3D self-supervised learning by constructing a conditional point generator…

Computer Vision and Pattern Recognition · Computer Science 2025-07-15 Yiyang Chen , Shanshan Zhao , Lunhao Duan , Changxing Ding , Dacheng Tao

The goal of scene text image super-resolution is to reconstruct high-resolution text-line images from unrecognizable low-resolution inputs. The existing methods relying on the optimization of pixel-level loss tend to yield text edges that…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Baolin Liu , Zongyuan Yang , Pengfei Wang , Junjie Zhou , Ziqi Liu , Ziyi Song , Yan Liu , Yongping Xiong

Concept erasure in text-to-image diffusion models is crucial for mitigating harmful content, yet existing methods often compromise generative quality. We introduce Semantic Surgery, a novel training-free, zero-shot framework for concept…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Lexiang Xiong , Chengyu Liu , Jingwen Ye , Yan Liu , Yuecong Xu

Recent strides in Text-to-3D techniques have been propelled by distilling knowledge from powerful large text-to-image diffusion models (LDMs). Nonetheless, existing Text-to-3D approaches often grapple with challenges such as…

Computer Vision and Pattern Recognition · Computer Science 2023-08-23 Yiwen Chen , Chi Zhang , Xiaofeng Yang , Zhongang Cai , Gang Yu , Lei Yang , Guosheng Lin

Text-driven 3D scene editing has gained significant attention owing to its convenience and user-friendliness. However, existing methods still lack accurate control of the specified appearance and location of the editing result due to the…

Computer Vision and Pattern Recognition · Computer Science 2024-04-26 Jingyu Zhuang , Di Kang , Yan-Pei Cao , Guanbin Li , Liang Lin , Ying Shan

A significant research effort is focused on exploiting the amazing capacities of pretrained diffusion models for the editing of images.They either finetune the model, or invert the image in the latent space of the pretrained model. However,…

Computer Vision and Pattern Recognition · Computer Science 2024-12-09 Senmao Li , Joost van de Weijer , Taihang Hu , Fahad Shahbaz Khan , Qibin Hou , Yaxing Wang , Jian Yang , Ming-Ming Cheng

Visual editing with diffusion models has made significant progress but often struggles with complex scenarios that textual guidance alone could not adequately describe, highlighting the need for additional non-text editing prompts. In this…

Computer Vision and Pattern Recognition · Computer Science 2025-08-29 Hyeonyu Kim , Seokhoon Jeong , Seonghee Han , Chanhyuk Choi , Taehwan Kim

Recent advances in text-guided image editing and 3D Gaussian Splatting (3DGS) have enabled high-quality 3D scene manipulation. However, existing pipelines rely on iterative edit-and-fit optimization at test time, alternating between 2D…

Computer Vision and Pattern Recognition · Computer Science 2026-04-23 Haitao Huang , Shin-Fang Chng , Huangying Zhan , Qingan Yan , Yi Xu

In light of recent breakthroughs in text-to-image (T2I) generation, particularly with diffusion transformers (DiT), subject-driven technologies are increasingly being employed for high-fidelity customized production that preserves subject…

Computer Vision and Pattern Recognition · Computer Science 2025-07-22 Yanbing Zhang , Zhe Wang , Qin Zhou , Mengping Yang

Instruction-guided generative models, especially those using text-to-image (T2I) and text-to-video (T2V) diffusion frameworks, have advanced the field of content editing in recent years. To extend these capabilities to 4D scene, we…

Computer Vision and Pattern Recognition · Computer Science 2025-04-02 Hasan Iqbal , Nazmul Karim , Umar Khalid , Azib Farooq , Zichun Zhong , Chen Chen , Jing Hua

Text-to-image generation has witnessed significant progress with the advent of diffusion models. Despite the ability to generate photorealistic images, current text-to-image diffusion models still often struggle to accurately interpret and…

Computer Vision and Pattern Recognition · Computer Science 2023-11-28 Tsung-Han Wu , Long Lian , Joseph E. Gonzalez , Boyi Li , Trevor Darrell

Text-guided image generation has advanced rapidly with large-scale diffusion models, yet achieving precise stylization with visual exemplars remains difficult. Existing approaches often depend on task-specific retraining or expensive…

Computer Vision and Pattern Recognition · Computer Science 2026-01-13 Yingying Deng , Xiangyu He , Fan Tang , Weiming Dong , Xucheng Yin

Image manipulation under the guidance of textual descriptions has recently received a broad range of attention. In this study, we focus on the regional editing of images with the guidance of given text prompts. Different from current…

Computer Vision and Pattern Recognition · Computer Science 2023-02-24 Nisha Huang , Fan Tang , Weiming Dong , Tong-Yee Lee , Changsheng Xu

Inspired by the software industry's practice of offering different editions or versions of a product tailored to specific user groups or use cases, we propose a novel task, namely, training-free editioning, for text-to-image models.…

Computer Vision and Pattern Recognition · Computer Science 2024-05-28 Jinqi Wang , Yunfei Fu , Zhangcan Ding , Bailin Deng , Yu-Kun Lai , Yipeng Qin

Image diffusion models have been utilized in various tasks, such as text-to-image generation and controllable image synthesis. Recent research has introduced tuning methods that make subtle adjustments to the original models, yielding…

Computer Vision and Pattern Recognition · Computer Science 2023-12-19 Zeyinzi Jiang , Chaojie Mao , Yulin Pan , Zhen Han , Jingfeng Zhang
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