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 126–150 of 427 papers

TitleStatusHype
RG-Flow: A hierarchical and explainable flow model based on renormalization group and sparse priorCode1
Two-stream Encoder-Decoder Network for Localizing Image ForgeriesCode1
Text as Neural Operator: Image Manipulation by Text InstructionCode1
Open-Edit: Open-Domain Image Manipulation with Open-Vocabulary InstructionsCode1
SPAN: Spatial Pyramid Attention Network for Image Manipulation LocalizationCode1
Image Shape Manipulation from a Single Augmented Training SampleCode1
Swapping Autoencoder for Deep Image ManipulationCode1
SRFlow: Learning the Super-Resolution Space with Normalizing FlowCode1
Conditional Image Generation and Manipulation for User-Specified ContentCode1
Fake face detection via adaptive manipulation traces extraction networkCode1
High Resolution Face Age EditingCode1
A Disentangling Invertible Interpretation Network for Explaining Latent RepresentationsCode1
SESAME: Semantic Editing of Scenes by Adding, Manipulating or Erasing ObjectsCode1
Semantic Image Manipulation Using Scene GraphsCode1
Self-Supervised Scene De-occlusionCode1
Exploiting Deep Generative Prior for Versatile Image Restoration and ManipulationCode1
Lifespan Age Transformation SynthesisCode1
Syn2Real: Forgery Classification via Unsupervised Domain AdaptationCode1
What Else Can Fool Deep Learning? Addressing Color Constancy Errors on Deep Neural Network PerformanceCode1
ManiGAN: Text-Guided Image ManipulationCode1
Kornia: an Open Source Differentiable Computer Vision Library for PyTorchCode1
MaskGAN: Towards Diverse and Interactive Facial Image ManipulationCode1
SinGAN: Learning a Generative Model from a Single Natural ImageCode1
Neural Imaging Pipelines - the Scourge or Hope of Forensics?Code1
Content Authentication for Neural Imaging Pipelines: End-to-end Optimization of Photo Provenance in Complex Distribution ChannelsCode1
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Benchmark Results

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