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 211–220 of 427 papers

TitleStatusHype
Beyond Fully Supervised Pixel Annotations: Scribble-Driven Weakly-Supervised Framework for Image Manipulation Localization—0
Blind Data Adaptation to tackle Covariate Shift in Operational Steganalysis—0
Boosting Image Forgery Detection using Resampling Features and Copy-move analysis—0
Bridging CLIP and StyleGAN through Latent Alignment for Image Editing—0
Can GPT tell us why these images are synthesized? Empowering Multimodal Large Language Models for Forensics—0
C-Flow: Conditional Generative Flow Models for Images and 3D Point Clouds—0
CIMGEN: Controlled Image Manipulation by Finetuning Pretrained Generative Models on Limited Data—0
CLIP-PAE: Projection-Augmentation Embedding to Extract Relevant Features for a Disentangled, Interpretable, and Controllable Text-Guided Face Manipulation—0
Closed-Loop Unsupervised Representation Disentanglement with β-VAE Distillation and Diffusion Probabilistic Feedback—0
CoIE: Chain-of-Instruct Editing for Multi-Attribute Face Manipulation—0
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Benchmark Results

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