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 351–400 of 427 papers

TitleStatusHype
SPN-CNN: Boosting Sensor-Based Source Camera Attribution With Deep Learning—0
BATINet: Background-Aware Text to Image Synthesis and Manipulation Network—0
A Visually Attentive Splice Localization Network with Multi-Domain Feature Extractor and Multi-Receptive Field Upsampler—0
Automated X-ray Image Analysis for Cargo Security: Critical Review and Future Promise—0
Auto-Focus Contrastive Learning for Image Manipulation Detection—0
A Unified Architecture of Semantic Segmentation and Hierarchical Generative Adversarial Networks for Expression Manipulation—0
Augmentation Techniques Analysis with Removal of Class Imbalance Using PyTorch for Intel Scene Dataset—0
Attribute-Specific Manipulation Based on Layer-Wise Channels—0
Visual Text Meets Low-level Vision: A Comprehensive Survey on Visual Text Processing—0
Attack to Fool and Explain Deep Networks—0
Adaptive adversarial training method for improving multi-scale GAN based on generalization bound theory—0
Volkit: A Performance-Portable Computer Vision Library for 3D Volumetric Data—0
Attack to Explain Deep Representation—0
A Survey of Deep Fake Detection for Trial Courts—0
A StyleMap-Based Generator for Real-Time Image Projection and Local Editing—0
A Skip Connection Architecture for Localization of Image Manipulations—0
Target-Free Text-guided Image Manipulation—0
Task-Oriented Diffusion Inversion for High-Fidelity Text-based Editing—0
TBNet:Two-Stream Boundary-aware Network for Generic Image Manipulation Localization—0
Application of deep learning to camera trap data for ecologists in planning / engineering -- Can captivity imagery train a model which generalises to the wild?—0
TextCLIP: Text-Guided Face Image Generation And Manipulation Without Adversarial Training—0
Anti-Inpainting: A Proactive Defense against Malicious Diffusion-based Inpainters under Unknown Conditions—0
Text-Driven Image Manipulation via Semantic-Aware Knowledge Transfer—0
Text-Guided Unsupervised Latent Transformation for Multi-Attribute Image Manipulation—0
WDRN : A Wavelet Decomposed RelightNet for Image Relighting—0
A Noise and Edge extraction-based dual-branch method for Shallowfake and Deepfake Localization—0
The Effect of Class Definitions on the Transferability of Adversarial Attacks Against Forensic CNNs—0
An Inpainting-Infused Pipeline for Attire and Background Replacement—0
The Misty Three Point Algorithm for Relative Pose—0
Towards Arbitrary Text-driven Image Manipulation via Space Alignment—0
Towards Controllable and Photorealistic Region-wise Image Manipulation—0
AnimeDL-2M: Million-Scale AI-Generated Anime Image Detection and Localization in Diffusion Era—0
Analysis of Adversarial Image Manipulations—0
Enhanced Controllability of Diffusion Models via Feature Disentanglement and Realism-Enhanced Sampling Methods—0
Towards Explainable Partial-AIGC Image Quality Assessment—0
Weakly-supervised Localization of Manipulated Image Regions Using Multi-resolution Learned Features—0
AIM 2024 Sparse Neural Rendering Challenge: Methods and Results—0
AIM 2024 Challenge on Video Super-Resolution Quality Assessment: Methods and Results—0
Towards Performance Improvement in Indian Sign Language Recognition—0
3D-Fixup: Advancing Photo Editing with 3D Priors—0
AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results—0
Towards Recovery of Conditional Vectors from Conditional Generative Adversarial Networks—0
Towards Reliable Identification of Diffusion-based Image Manipulations—0
Towards the Detection of AI-Synthesized Human Face Images—0
Hierarchical Diffusion Autoencoders and Disentangled Image Manipulation—0
Highly Personalized Text Embedding for Image Manipulation by Stable Diffusion—0
TrainFors: A Large Benchmark Training Dataset for Image Manipulation Detection and Localization—0
Having your cake and eating it too: Scripted workflows for image manipulation—0
Training Free Guided Flow Matching with Optimal Control—0
Holistic Image Manipulation Detection using Pixel Co-occurrence Matrices—0
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Benchmark Results

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