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

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Showing 201–225 of 427 papers

TitleStatusHype
Towards Effective Image Manipulation Detection with Proposal Contrastive LearningCode1
One Model to Edit Them All: Free-Form Text-Driven Image Manipulation with Semantic ModulationsCode1
Leveraging Off-the-shelf Diffusion Model for Multi-attribute Fashion Image Manipulation—0
Bridging CLIP and StyleGAN through Latent Alignment for Image Editing—0
CLIP-PAE: Projection-Augmentation Embedding to Extract Relevant Features for a Disentangled, Interpretable, and Controllable Text-Guided Face Manipulation—0
LDEdit: Towards Generalized Text Guided Image Manipulation via Latent Diffusion Models—0
CFL-Net: Image Forgery Localization Using Contrastive LearningCode0
Robust Sound-Guided Image Manipulation—0
Selective manipulation of disentangled representations for privacy-aware facial image processing—0
Unsupervised Structure-Consistent Image-to-Image Translation—0
Language-Guided Face Animation by Recurrent StyleGAN-based GeneratorCode1
Supervised Attribute Information Removal and Reconstruction for Image ManipulationCode0
Towards Counterfactual Image Manipulation via CLIPCode1
Noise and Edge Based Dual Branch Image Manipulation DetectionCode1
Rethinking Adversarial Examples for Location Privacy Protection—0
Unsupervised Image Representation Learning with Deep Latent ParticlesCode1
A Survey of Deep Fake Detection for Trial Courts—0
Splicing Detection and Localization In Satellite Imagery Using Conditional GANs—0
AugStatic - A Light-Weight Image Augmentation LibraryCode0
Improving Model Performance and Removing the Class Imbalance Problem Using Augmentation—0
Deep PCB To COCO ConvertorCode2
Augmented Balanced Image Dataset Generator Using AugStatic LibraryCode0
Augmentation Techniques Analysis with Removal of Class Imbalance Using PyTorch for Intel Scene Dataset—0
Resnet18 Model With Sequential Layer For Computing Accuracy On Image Classification Dataset—0
Detecting Recolored Image by Spatial Correlation—0
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Benchmark Results

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