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Image Manipulation
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Image Manipulation is the process of altering or transforming an existing image to achieve a desired effect or to modify its content. This can involve various techniques and tools to enhance, modify, or create images based on specific requirements.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Varying Manifolds in Diffusion: From Time-varying Geometries to Visual Saliency
Blind Data Adaptation to tackle Covariate Shift in Operational Steganalysis
EmoEdit: Evoking Emotions through Image Manipulation
SEED-Data-Edit Technical Report: A Hybrid Dataset for Instructional Image Editing
Deep Image Restoration For Image Anti-Forensics
Research on Splicing Image Detection Algorithms Based on Natural Image Statistical Characteristics
ClickDiffusion: Harnessing LLMs for Interactive Precise Image Editing
Deep Image Composition Meets Image Forgery
Grid Diffusion Models for Text-to-Video Generation
ReNoise: Real Image Inversion Through Iterative Noising
Generalized Consistency Trajectory Models for Image Manipulation
DreamSampler: Unifying Diffusion Sampling and Score Distillation for Image Manipulation
FKA-Owl: Advancing Multimodal Fake News Detection through Knowledge-Augmented LVLMs
Towards the Detection of AI-Synthesized Human Face Images
Exploring Saliency Bias in Manipulation Detection
Visual Text Meets Low-level Vision: A Comprehensive Survey on Visual Text Processing
An Inpainting-Infused Pipeline for Attire and Background Replacement
Point and Instruct: Enabling Precise Image Editing by Unifying Direct Manipulation and Text Instructions
Closed-Loop Unsupervised Representation Disentanglement with $β$-VAE Distillation and Diffusion Probabilistic Feedback
Repositioning the Subject within Image
Learning to Manipulate Artistic Images
CIMGEN: Controlled Image Manipulation by Finetuning Pretrained Generative Models on Limited Data
Key-point Guided Deformable Image Manipulation Using Diffusion Model
A Visually Attentive Splice Localization Network with Multi-Domain Feature Extractor and Multi-Receptive Field Upsampler
PROMPT-IML: Image Manipulation Localization with Pre-trained Foundation Models Through Prompt Tuning
DETER: Detecting Edited Regions for Deterring Generative Manipulations
CoIE: Chain-of-Instruct Editing for Multi-Attribute Face Manipulation
Diffusion Cocktail: Mixing Domain-Specific Diffusion Models for Diversified Image Generations
Inversion-Free Image Editing with Natural Language
LEGO: Learning EGOcentric Action Frame Generation via Visual Instruction Tuning
MMFusion: Combining Image Forensic Filters for Visual Manipulation Detection and Localization
Rethinking Image Editing Detection in the Era of Generative AI Revolution
LEDITS++: Limitless Image Editing using Text-to-Image Models
A New Benchmark and Model for Challenging Image Manipulation Detection
PRISM: Progressive Restoration for Scene Graph-based Image Manipulation
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