Image Manipulation
157 papers with code • 1 benchmarks • 4 datasets
Libraries
Use these libraries to find Image Manipulation models and implementations
CelebAMask-HQ
LRS2
CASIA V2
Satire Dataset
Latest papers with no code
ReNoise: Real Image Inversion Through Iterative Noising
However, applying these methods to real images necessitates the inversion of the images into the domain of the pretrained diffusion model.
DreamSampler: Unifying Diffusion Sampling and Score Distillation for Image Manipulation
Reverse sampling and score-distillation have emerged as main workhorses in recent years for image manipulation using latent diffusion models (LDMs).
Towards the Detection of AI-Synthesized Human Face Images
However, the problem of detecting purely synthesized face images has been explored to a lesser extent.
Exploring Saliency Bias in Manipulation Detection
The social media-fuelled explosion of fake news and misinformation supported by tampered images has led to growth in the development of models and datasets for image manipulation detection.
An Inpainting-Infused Pipeline for Attire and Background Replacement
In recent years, groundbreaking advancements in Generative Artificial Intelligence (GenAI) have triggered a transformative paradigm shift, significantly influencing various domains.
Point and Instruct: Enabling Precise Image Editing by Unifying Direct Manipulation and Text Instructions
This allows users to benefit from both the visual descriptiveness of natural language and the spatial precision of direct manipulation.
Closed-Loop Unsupervised Representation Disentanglement with $β$-VAE Distillation and Diffusion Probabilistic Feedback
Representation disentanglement may help AI fundamentally understand the real world and thus benefit both discrimination and generation tasks.
CIMGEN: Controlled Image Manipulation by Finetuning Pretrained Generative Models on Limited Data
Content creation and image editing can benefit from flexible user controls.
Key-point Guided Deformable Image Manipulation Using Diffusion Model
In this paper, we introduce a Key-point-guided Diffusion probabilistic Model (KDM) that gains precise control over images by manipulating the object's key-point.
A Visually Attentive Splice Localization Network with Multi-Domain Feature Extractor and Multi-Receptive Field Upsampler
In this work, a novel, "Visually Attentive Splice Localization Network with Multi-Domain Feature Extractor and Multi-Receptive Field Upsampler" has been proposed.
