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Found 11 papers, 3 papers with code
SafeGen: Mitigating Unsafe Content Generation in Text-to-Image Models
The key idea is to eliminate unsafe visual representations from the model regardless of the text input.
CamPro: Camera-based Anti-Facial Recognition
The proliferation of images captured from millions of cameras and the advancement of facial recognition (FR) technology have made the abuse of FR a severe privacy threat.
TPatch: A Triggered Physical Adversarial Patch
Evaluations with three object detectors, YOLO V3/V5 and Faster R-CNN, and eight image classifiers demonstrate the effectiveness of TPatch in both the simulation and the real world.
Exploring Adversarial Robustness of LiDAR-Camera Fusion Model in Autonomous Driving
Our study assesses the adversarial robustness of LiDAR-camera fusion models in 3D object detection.
Catch You and I Can: Revealing Source Voiceprint Against Voice Conversion
Voice conversion (VC) techniques can be abused by malicious parties to transform their audios to sound like a target speaker, making it hard for a human being or a speaker verification/identification system to trace the source speaker.
V-Cloak: Intelligibility-, Naturalness- & Timbre-Preserving Real-Time Voice Anonymization
Apart from the anonymity loss, we further incorporate the intelligibility loss and the psychoacoustics-based naturalness loss.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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Private Eye: On the Limits of Textual Screen Peeking via Eyeglass Reflections in Video Conferencing
Our models and experimental results in a controlled lab setting show it is possible to reconstruct and recognize with over 75% accuracy on-screen texts that have heights as small as 10 mm with a 720p webcam.
Rolling Colors: Adversarial Laser Exploits against Traffic Light Recognition
By exploiting the rolling shutter of CMOS sensors, we manage to inject a color stripe overlapped on the traffic light in the image, which can cause a red light to be recognized as a green light or vice versa.
FakeWake: Understanding and Mitigating Fake Wake-up Words of Voice Assistants
In the area of Internet of Things (IoT) voice assistants have become an important interface to operate smart speakers, smartphones, and even automobiles.
Tips and Tricks for Webly-Supervised Fine-Grained Recognition: Learning from the WebFG 2020 Challenge
WebFG 2020 is an international challenge hosted by Nanjing University of Science and Technology, University of Edinburgh, Nanjing University, The University of Adelaide, Waseda University, etc.
Channel Pruning Guided by Spatial and Channel Attention for DNNs in Intelligent Edge Computing
Guided by the scale values generated by SCA for measuring channel importance, we further propose a new channel pruning approach called Channel Pruning guided by Spatial and Channel Attention (CPSCA).
