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Found 15 papers, 9 papers with code
Mitigating Feature Gap for Adversarial Robustness by Feature Disentanglement
Deep neural networks are vulnerable to adversarial samples.
Masked Attribute Description Embedding for Cloth-Changing Person Re-identification
To address this, we mask the clothing and color information in the personal attribute description extracted through an attribute detection model.
Adv-Diffusion: Imperceptible Adversarial Face Identity Attack via Latent Diffusion Model
Adversarial attacks involve adding perturbations to the source image to cause misclassification by the target model, which demonstrates the potential of attacking face recognition models.
Symmetrical Bidirectional Knowledge Alignment for Zero-Shot Sketch-Based Image Retrieval
In this paper, we propose a novel Symmetrical Bidirectional Knowledge Alignment for zero-shot sketch-based image retrieval (SBKA).
DeepFidelity: Perceptual Forgery Fidelity Assessment for Deepfake Detection
Considering the complexity of the quality distribution of both real and fake faces, we propose a novel Deepfake detection framework named DeepFidelity to adaptively distinguish real and fake faces with varying image quality by mining the perceptual forgery fidelity of face images.
GazeForensics: DeepFake Detection via Gaze-guided Spatial Inconsistency Learning
DeepFake detection is pivotal in personal privacy and public safety.
Toward Trustworthy Identity Tracing via Multi-attribute Synergistic Identification
Based on the proposed identity model, we propose a trustworthy identity tracing framework (TITF) with multi-attribute synergistic identification to determine the identity of unknown objects, which can optimize the core identification set and provide an interpretable identity tracing process.
Enhancing Robust Representation in Adversarial Training: Alignment and Exclusion Criteria
Deep neural networks are vulnerable to adversarial noise.
Ranked #1 on
Adversarial Attack
on CIFAR-10
(Attack: AutoAttack metric)
Gradient constrained sharpness-aware prompt learning for vision-language models
This paper targets a novel trade-off problem in generalizable prompt learning for vision-language models (VLM), i. e., improving the performance on unseen classes while maintaining the performance on seen classes.
Attention Consistency Refined Masked Frequency Forgery Representation for Generalizing Face Forgery Detection
Due to the successful development of deep image generation technology, visual data forgery detection would play a more important role in social and economic security.
MMNet: Multi-Collaboration and Multi-Supervision Network for Sequential Deepfake Detection
Advanced manipulation techniques have provided criminals with opportunities to make social panic or gain illicit profits through the generation of deceptive media, such as forged face images.
Hierarchical Forgery Classifier On Multi-modality Face Forgery Clues
Face forgery detection plays an important role in personal privacy and social security.
FedForgery: Generalized Face Forgery Detection with Residual Federated Learning
Experiments conducted on publicly available face forgery detection datasets prove the superior performance of the proposed FedForgery.
TransFA: Transformer-based Representation for Face Attribute Evaluation
The multiple branches transformer is employed to explore the inter-correlation between different attributes in similar semantic regions for attribute feature learning.
Spatial-Temporal Frequency Forgery Clue for Video Forgery Detection in VIS and NIR Scenario
In recent years, with the rapid development of face editing and generation, more and more fake videos are circulating on social media, which has caused extreme public concerns.
