SOTAVerified

Image Manipulation

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.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 401–425 of 427 papers

TitleStatusHype
HRFNet: High-Resolution Forgery Network for Localizing Satellite Image Manipulation—0
HRGR: Enhancing Image Manipulation Detection via Hierarchical Region-aware Graph Reasoning—0
Grid Diffusion Models for Text-to-Video Generation—0
GPU-Accelerated Mobile Multi-view Style Transfer—0
GMFIM: A Generative Mask-guided Facial Image Manipulation Model for Privacy Preservation—0
ImageBrush: Learning Visual In-Context Instructions for Exemplar-Based Image Manipulation—0
TriPINet: Tripartite Progressive Integration Network for Image Manipulation Localization—0
GIMP-ML: Python Plugins for using Computer Vision Models in GIMP—0
Image Manipulation via Multi-Hop Instructions -- A New Dataset and Weakly-Supervised Neuro-Symbolic Approach—0
Image Manipulation with Natural Language using Two-sidedAttentive Conditional Generative Adversarial Network—0
Image Manipulation with Perceptual Discriminators—0
TruFor: Leveraging all-round clues for trustworthy image forgery detection and localization—0
GIMP and Wavelets for Medical Image Processing: Enhancing Images of the Fundus of the Eye—0
Fashion Editing with Adversarial Parsing Learning—0
Image Splicing Detection via Camera Response Function Analysis—0
Generative Autoregressive Ensembles for Satellite Imagery Manipulation Detection—0
IMDPrompter: Adapting SAM to Image Manipulation Detection by Cross-View Automated Prompt Learning—0
Generative Adversarial U-Net for Domain-free Medical Image Augmentation—0
Impact of Image Context for Single Deep Learning Face Morphing Attack Detection—0
Improved Semantic Inpainting Architecture Augmented with a Facial Landmark Detector—0
AIM 2019 Challenge on Image Demoireing: Methods and Results—0
Improving Model Performance and Removing the Class Imbalance Problem Using Augmentation—0
Incorporating Ensemble and Transfer Learning For An End-To-End Auto-Colorized Image Detection Model—0
GBSD: Generative Bokeh with Stage Diffusion—0
Instruction-based Image Manipulation by Watching How Things Move—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Pix2PixHD-SIALPIPS (S1)0.44—Unverified
2TPSLPIPS (S1)0.12—Unverified