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Found 12 papers, 1 papers with code
Parameter-Saving Adversarial Training: Reinforcing Multi-Perturbation Robustness via Hypernetworks
Adversarial training serves as one of the most popular and effective methods to defend against adversarial perturbations.
Stealthy Physical Masked Face Recognition Attack via Adversarial Style Optimization
Moreover, to ameliorate the phenomenon of sub-optimization with one fixed style, we propose to discover the optimal style given a target through style optimization in a continuous relaxation manner.
Reducing Adversarial Training Cost with Gradient Approximation
Deep learning models have achieved state-of-the-art performances in various domains, while they are vulnerable to the inputs with well-crafted but small perturbations, which are named after adversarial examples (AEs).
TransFlow: Transformer as Flow Learner
Optical flow is an indispensable building block for various important computer vision tasks, including motion estimation, object tracking, and disparity measurement.
Two-in-one Knowledge Distillation for Efficient Facial Forgery Detection
More specifically, knowledge distillation on both the spatial and frequency branches has degraded performance than distillation only on the spatial branch.
Anti-Compression Contrastive Facial Forgery Detection
To enhance the performance for such models, we consider the weak compressed and strong compressed data as two views of the original data and they should have similar representation and relationships with other samples.
Private Image Generation With Dual-Purpose Auxiliary Classifier
However, apart from this standard utility, we identify the "reversed utility" as another crucial aspect, which computes the accuracy on generated data of a classifier trained using real data, dubbed as real2gen accuracy (r2g%).
Solve the Puzzle of Instance Segmentation in Videos: A Weakly Supervised Framework with Spatio-Temporal Collaboration
Instance segmentation in videos, which aims to segment and track multiple objects in video frames, has garnered a flurry of research attention in recent years.
DeepFake Disrupter: The Detector of DeepFake Is My Friend
We argue that the detectors do not share a similar perspective as human eyes, which might still be spoofed by the disrupted data.
Wideband Channel Estimation for IRS-Aided Systems in the Face of Beam Squint
Intelligent reflecting surfaces (IRSs) improve both the bandwidth and energy efficiency of wideband communication systems by using low-cost passive elements for reflecting the impinging signals with adjustable phase shifts.
Backdoor Attacks and Countermeasures on Deep Learning: A Comprehensive Review
We have also reviewed the flip side of backdoor attacks, which are explored for i) protecting intellectual property of deep learning models, ii) acting as a honeypot to catch adversarial example attacks, and iii) verifying data deletion requested by the data contributor. Overall, the research on defense is far behind the attack, and there is no single defense that can prevent all types of backdoor attacks.
Revocable Federated Learning: A Benchmark of Federated Forest
A learning federation is composed of multiple participants who use the federated learning technique to collaboratively train a machine learning model without directly revealing the local data.
