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Image Manipulation
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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.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
SPN-CNN: Boosting Sensor-Based Source Camera Attribution With Deep Learning
Syn2Real: Forgery Classification via Unsupervised Domain Adaptation
Scientific Image Tampering Detection Based On Noise Inconsistencies: A Method And Datasets
Image Manipulation with Natural Language using Two-sidedAttentive Conditional Generative Adversarial Network
What Else Can Fool Deep Learning? Addressing Color Constancy Errors on Deep Neural Network Performance
C-Flow: Conditional Generative Flow Models for Images and 3D Point Clouds
Image Processing Using Multi-Code GAN Prior
ManiGAN: Text-Guided Image Manipulation
Unconstrained Facial Expression Transfer using Style-based Generator
Natural Image Manipulation for Autoregressive Models Using Fisher Scores
DLGAN: Disentangling Label-Specific Fine-Grained Features for Image Manipulation
Constrained R-CNN: A general image manipulation detection model
Copy-Move Forgery Classification via Unsupervised Domain Adaptation
AIM 2019 Challenge on Image Demoireing: Methods and Results
AIM 2019 Challenge on Image Demoireing: Dataset and Study
Effectiveness of random deep feature selection for securing image manipulation detectors against adversarial examples
Kornia: an Open Source Differentiable Computer Vision Library for PyTorch
Photorealistic Material Editing Through Direct Image Manipulation
MaskGAN: Towards Diverse and Interactive Facial Image Manipulation
Interpreting the Latent Space of GANs for Semantic Face Editing
Style Generator Inversion for Image Enhancement and Animation
DualDis: Dual-Branch Disentangling with Adversarial Learning
Fashion Editing with Adversarial Parsing Learning
FaceShapeGene: A Disentangled Shape Representation for Flexible Face Image Editing
SinGAN: Learning a Generative Model from a Single Natural Image
Lifting AutoEncoders: Unsupervised Learning of a Fully-Disentangled 3D Morphable Model using Deep Non-Rigid Structure from Motion
Towards Photographic Image Manipulation with Balanced Growing of Generative Autoencoders
Unsupervised Person Image Generation with Semantic Parsing Transformation
Point-to-Point Video Generation
Neural Imaging Pipelines - the Scourge or Hope of Forensics?
Cross-Domain Image Manipulation by Demonstration
Content Authentication for Neural Imaging Pipelines: End-to-end Optimization of Photo Provenance in Complex Distribution Channels
SEIGAN: Towards Compositional Image Generation by Simultaneously Learning to Segment, Enhance, and Inpaint
Image Smoothing via Unsupervised Learning
Image Manipulation with Perceptual Discriminators
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