Papers Text-based Image Editing
“Text-based Image Editing” 태그가 달린 논문 54편 · 필터 해제
Proc3D: Procedural 3D Generation and Parametric Editing of 3D Shapes with Large Language Models
Generating 3D models has traditionally been a complex task requiring specialized expertise. While recent advances in generative AI have sought to automate this process, existing methods produce non-editable representatio…
Text-based Image Editing3D GenerationPoint CloudsVENUS: Visual Editing with Noise Inversion Using Scene Graphs
State-of-the-art text-based image editing models often struggle to balance background preservation with semantic consistency, frequently resulting either in the synthesis of entirely new images or in outputs that fail to…
Text-based Image EditingFlowDC: Flow-Based Decoupling-Decay for Complex Image Editing
With the surge of pre-trained text-to-image flow matching models, text-based image editing performance has gained remarkable improvement, especially for \underline{simple editing} that only contains a single editing targ…
Text-based Image Editing3D-Consistent Multi-View Editing by Correspondence Guidance
Recent advancements in diffusion and flow models have greatly improved text-based image editing, yet methods that edit images independently often produce geometrically and photometrically inconsistent results across diff…
Text-based Image EditingTarget-aware Image Editing via Cycle-consistent Constraints
Recent pre-trained text-to-image flow models have enabled remarkable progress in text-based image editing. Mainstream approaches adopt a corruption-then-restoration paradigm, where the source image is first corrupted int…
Text-based Image EditingImage ReconstructionInstructUDrag: Joint Text Instructions and Object Dragging for Interactive Image Editing
Text-to-image diffusion models have shown great potential for image editing, with techniques such as text-based and object-dragging methods emerging as key approaches. However, each of these methods has inherent limitati…
Text-based Image EditingImage ReconstructionPrompt-to-Prompt: Text-Based Image Editing Via Cross-Attention Mechanisms -- The Research of Hyperparameters and Novel Mechanisms to Enhance Existing Frameworks
Recent advances in image editing have shifted from manual pixel manipulation to employing deep learning methods like stable diffusion models, which now leverage cross-attention mechanisms for text-driven control. This tr…
Text-based Image EditingImmunizing Images from Text to Image Editing via Adversarial Cross-Attention
Recent advances in text-based image editing have enabled fine-grained manipulation of visual content guided by natural language. However, such methods are susceptible to adversarial attacks. In this work, we propose a no…
Text-based Image EditingDiscrete Noise Inversion for Next-scale Autoregressive Text-based Image Editing
Visual autoregressive models (VAR) have recently emerged as a promising class of generative models, achieving performance comparable to diffusion models in text-to-image generation tasks. While conditional generation has…
Text-based Image EditingText-to-Image GenerationNoHumansRequired: Autonomous High-Quality Image Editing Triplet Mining
Recent advances in generative modeling enable image editing assistants that follow natural language instructions without additional user input. Their supervised training requires millions of triplets: original image, ins…
Image EditingText-based Image EditingTripletCora: Correspondence-aware image editing using few step diffusion
Image editing is an important task in computer graphics, vision, and VFX, with recent diffusion-based methods achieving fast and high-quality results. However, edits requiring significant structural changes, such as non-…
Image-to-Image TranslationSemantic correspondenceText-based Image EditingTranslationPOEM: Precise Object-level Editing via MLLM control
Diffusion models have significantly improved text-to-image generation, producing high-quality, realistic images from textual descriptions. Beyond generation, object-level image editing remains a challenging problem, requ…
Image GenerationObjectObject LocalizationText-based Image Editing+2ILLUME+: Illuminating Unified MLLM with Dual Visual Tokenization and Diffusion Refinement
We present ILLUME+ that leverages dual visual tokenization and a diffusion decoder to improve both deep semantic understanding and high-fidelity image generation. Existing unified models have struggled to simultaneously …
DecoderImage GenerationImage ReconstructionSuper-Resolution+2KV-Edit: Training-Free Image Editing for Precise Background Preservation
Background consistency remains a significant challenge in image editing tasks. Despite extensive developments, existing works still face a trade-off between maintaining similarity to the original image and generating con…
Text-based Image EditingPartEdit: Fine-Grained Image Editing using Pre-Trained Diffusion Models
We present the first text-based image editing approach for object parts based on pre-trained diffusion models. Diffusion-based image editing approaches capitalized on the deep understanding of diffusion models of image s…
ObjectText-based Image EditingFeedEdit: Text-Based Image Editing with Dynamic Feedback Regulation
Text-based image editing which aims at generating rigid or non-rigid changes to images conditioned on the given text, has recently attracted considerable interest. Previous works mainly follow the multi-step denoisin…
DenoisingText-based Image EditingFireFlow: Fast Inversion of Rectified Flow for Image Semantic Editing
Though Rectified Flows (ReFlows) with distillation offers a promising way for fast sampling, its fast inversion transforms images back to structured noise for recovery and following editing remains unsolved. This paper i…
Text-based Image EditingAction-based image editing guided by human instructions
Text-based image editing is typically approached as a static task that involves operations such as inserting, deleting, or modifying elements of an input image based on human instructions. Given the static nature of this…
Text-based Image EditingLoRA of Change: Learning to Generate LoRA for the Editing Instruction from A Single Before-After Image Pair
In this paper, we propose the LoRA of Change (LoC) framework for image editing with visual instructions, i.e., before-after image pairs. Compared to the ambiguities, insufficient specificity, and diverse interpretations …
SpecificityText-based Image EditingPathways on the Image Manifold: Image Editing via Video Generation
Recent advances in image editing, driven by image diffusion models, have shown remarkable progress. However, significant challenges remain, as these models often struggle to follow complex edit instructions accurately an…
Text-based Image EditingVideo Generation