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Image Attribution
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Image attribution algorithms aim to identify important regions that are highly relevant to model decisions.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
WILD: a new in-the-Wild Image Linkage Dataset for synthetic image attribution
LoRAX: LoRA eXpandable Networks for Continual Synthetic Image Attribution
Are handcrafted filters helpful for attributing AI-generated images?
I2AM: Interpreting Image-to-Image Latent Diffusion Models via Attribution Maps
BOSC: A Backdoor-based Framework for Open Set Synthetic Image Attribution
Hide and Seek: How Does Watermarking Impact Face Recognition?
Detecting Origin Attribution for Text-to-Image Diffusion Models
Less is More: Fewer Interpretable Region via Submodular Subset Selection
A Siamese-based Verification System for Open-set Architecture Attribution of Synthetic Images
What the DAAM: Interpreting Stable Diffusion Using Cross Attention
RepMix: Representation Mixing for Robust Attribution of Synthesized Images
Making Sense of Dependence: Efficient Black-box Explanations Using Dependence Measure
Deepfake Network Architecture Attribution
ARIA: Adversarially Robust Image Attribution for Content Provenance
OSCAR-Net: Object-centric Scene Graph Attention for Image Attribution
Learning to Disentangle GAN Fingerprint for Fake Image Attribution
Reverse Engineering of Generative Models: Inferring Model Hyperparameters from Generated Images
Gifsplanation via Latent Shift: A Simple Autoencoder Approach to Counterfactual Generation for Chest X-rays
Attributing Fake Images to GANs: Learning and Analyzing GAN Fingerprints
RISE: Randomized Input Sampling for Explanation of Black-box Models
A Unified Approach to Interpreting Model Predictions
Axiomatic Attribution for Deep Networks
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.