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Papers Text-based Image Editing

“Text-based Image Editing” 태그가 달린 논문 54편 · 필터 해제

Stable Flow: Vital Layers for Training-Free Image Editing

2024-11-21 · CVPR 2025 1 · Omri Avrahami, Or Patashnik, Ohad Fried, Egor Nemchinov 외

Diffusion models have revolutionized the field of content synthesis and editing. Recent models have replaced the traditional UNet architecture with the Diffusion Transformer (DiT), and employed flow-matching for improved…

Text-based Image Editing

Vision-guided and Mask-enhanced Adaptive Denoising for Prompt-based Image Editing

2024-10-14 · Kejie Wang, Xuemeng Song, Meng Liu, Jin Yuan 외

Text-to-image diffusion models have demonstrated remarkable progress in synthesizing high-quality images from text prompts, which boosts researches on prompt-based image editing that edits a source image according to a t…

DenoisingImage GenerationText-based Image Editing

Pixel Is Not A Barrier: An Effective Evasion Attack for Pixel-Domain Diffusion Models

2024-08-21 · Chun-Yen Shih, Li-Xuan Peng, Jia-Wei Liao, Ernie Chu 외

Diffusion Models have emerged as powerful generative models for high-quality image synthesis, with many subsequent image editing techniques based on them. However, the ease of text-based image editing introduces signific…

DenoisingImage GenerationText-based Image Editing

TurboEdit: Instant text-based image editing

2024-08-14 · Zongze Wu, Nicholas Kolkin, Jonathan Brandt, Richard Zhang 외

We address the challenges of precise image inversion and disentangled image editing in the context of few-step diffusion models. We introduce an encoder based iterative inversion technique. The inversion network is condi…

AttributeText-based Image Editing

Specify and Edit: Overcoming Ambiguity in Text-Based Image Editing

2024-07-29 · Ekaterina Iakovleva, Fabio Pizzati, Philip Torr, Stéphane Lathuilière

Text-based editing diffusion models exhibit limited performance when the user's input instruction is ambiguous. To solve this problem, we propose $\textit{Specify ANd Edit}$ (SANE), a zero-shot inference pipeline for dif…

DenoisingDiversityLanguage ModelingLanguage Modelling+2

FlexiEdit: Frequency-Aware Latent Refinement for Enhanced Non-Rigid Editing

2024-07-25 · Gwanhyeong Koo, Sunjae Yoon, Ji Woo Hong, Chang D. Yoo

Current image editing methods primarily utilize DDIM Inversion, employing a two-branch diffusion approach to preserve the attributes and layout of the original image. However, these methods encounter challenges with non-…

Text-based Image Editing

TIE: Revolutionizing Text-based Image Editing for Complex-Prompt Following and High-Fidelity Editing

2024-05-27 · Xinyu Zhang, Mengxue Kang, Fei Wei, Shuang Xu 외

As the field of image generation rapidly advances, traditional diffusion models and those integrated with multimodal large language models (LLMs) still encounter limitations in interpreting complex prompts and preserving…

Image GenerationText-based Image Editing

Paint by Inpaint: Learning to Add Image Objects by Removing Them First

2024-04-28 · CVPR 2025 1 · Navve Wasserman, Noam Rotstein, Roy Ganz, Ron Kimmel

Image editing has advanced significantly with the introduction of text-conditioned diffusion models. Despite this progress, seamlessly adding objects to images based on textual instructions without requiring user-provide…

Image InpaintingLanguage ModelingLanguage ModellingLarge Language Model+3

E4C: Enhance Editability for Text-Based Image Editing by Harnessing Efficient CLIP Guidance

2024-03-15 · Tianrui Huang, Pu Cao, Lu Yang, Chun Liu 외

Diffusion-based image editing is a composite process of preserving the source image content and generating new content or applying modifications. While current editing approaches have made improvements under text guidanc…

Text-based Image Editing

Doubly Abductive Counterfactual Inference for Text-based Image Editing

2024-03-05 · CVPR 2024 1 · Xue Song, Jiequan Cui, Hanwang Zhang, Jingjing Chen 외

We study text-based image editing (TBIE) of a single image by counterfactual inference because it is an elegant formulation to precisely address the requirement: the edited image should retain the fidelity of the origina…

counterfactualCounterfactual InferenceStyle TransferText-based Image Editing

Minecraft-ify: Minecraft Style Image Generation with Text-guided Image Editing for In-Game Application

2024-02-08 · Bumsoo Kim, Sanghyun Byun, Yonghoon Jung, Wonseop Shin 외

In this paper, we first present the character texture generation system \textit{Minecraft-ify}, specified to Minecraft video game toward in-game application. Ours can generate face-focused image for texture mapping tailo…

Image GenerationMinecraftText-based Image Editingtext-guided-image-editing+1

Wavelet-Guided Acceleration of Text Inversion in Diffusion-Based Image Editing

2024-01-18 · Gwanhyeong Koo, Sunjae Yoon, Chang D. Yoo

In the field of image editing, Null-text Inversion (NTI) enables fine-grained editing while preserving the structure of the original image by optimizing null embeddings during the DDIM sampling process. However, the NTI …

Text-based Image Editing

SpecRef: A Fast Training-free Baseline of Specific Reference-Condition Real Image Editing

2024-01-07 · Songyan Chen, Jiancheng Huang

Text-conditional image editing based on large diffusion generative model has attracted the attention of both the industry and the research community. Most existing methods are non-reference editing, with the user only ab…

Multimodel-guided image editingText-based Image Editingtext-guided-image-editingText-to-Image Generation

Inversion-Free Image Editing with Natural Language

2023-12-07 · Sihan Xu, Yidong Huang, Jiayi Pan, Ziqiao Ma 외

Despite recent advances in inversion-based editing, text-guided image manipulation remains challenging for diffusion models. The primary bottlenecks include 1) the time-consuming nature of the inversion process; 2) the s…

Image ManipulationText-based Image Editing

Direct Inversion: Boosting Diffusion-based Editing with 3 Lines of Code

2023-10-02 · Xuan Ju, Ailing Zeng, Yuxuan Bian, Shaoteng Liu 외

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…

Image GenerationText-based Image Editing

Dynamic Prompt Learning: Addressing Cross-Attention Leakage for Text-Based Image Editing

2023-09-27 · NeurIPS 2023 11 · Kai Wang, Fei Yang, Shiqi Yang, Muhammad Atif Butt 외

Large-scale text-to-image generative models have been a ground-breaking development in generative AI, with diffusion models showing their astounding ability to synthesize convincing images following an input text prompt.…

Prompt LearningText-based Image Editing

Controlling Geometric Abstraction and Texture for Artistic Images

2023-07-31 · Martin Büßemeyer, Max Reimann, Benito Buchheim, Amir Semmo 외

We present a novel method for the interactive control of geometric abstraction and texture in artistic images. Previous example-based stylization methods often entangle shape, texture, and color, while generative methods…

Image GenerationImage StylizationParameter PredictionStyle Transfer+1

Differential Diffusion: Giving Each Pixel Its Strength

2023-06-01 · Eran Levin, Ohad Fried

Diffusion models have revolutionized image generation and editing, producing state-of-the-art results in conditioned and unconditioned image synthesis. While current techniques enable user control over the degree of chan…

Image GenerationText-based Image Editing

LANCE: Stress-testing Visual Models by Generating Language-guided Counterfactual Images

2023-05-30 · NeurIPS 2023 11 · Viraj Prabhu, Sriram Yenamandra, Prithvijit Chattopadhyay, Judy Hoffman

We propose an automated algorithm to stress-test a trained visual model by generating language-guided counterfactual test images (LANCE). Our method leverages recent progress in large language modeling and text-based ima…

counterfactualLanguage ModelingLanguage ModellingSensitivity+1

Negative-prompt Inversion: Fast Image Inversion for Editing with Text-guided Diffusion Models

2023-05-26 · Daiki Miyake, Akihiro Iohara, Yu Saito, Toshiyuki Tanaka

In image editing employing diffusion models, it is crucial to preserve the reconstruction fidelity to the original image while changing its style. Although existing methods ensure reconstruction fidelity through optimiza…

Text-based Image Editing
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