1.5k citations · 3.1k across the 169 of their papers we have counts for
15 papers · 1 filter
PaniCar: Securing the Perception of Advanced Driving Assistance Systems Against Emergency Vehicle Lighting
Elad Feldman, Jacob Shams, Dudi Biton +7
The safety of autonomous cars has come under scrutiny in recent years, especially after 16 documented incidents involving Teslas (with autopilot engaged) crashing into parked emerg…
A Privacy Enhancing Technique to Evade Detection by Street Video Cameras Without Using Adversarial Accessories
Jacob Shams, Ben Nassi, Satoru Koda +2
In this paper, we propose a privacy-enhancing technique leveraging an inherent property of automatic pedestrian detection algorithms, namely, that the training of deep neural netwo…
Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World
Dudi Biton, Jacob Shams, Satoru Koda +3
The traditional learning process of patch-based adversarial attacks, conducted in the digital domain and then applied in the physical domain (e.g., via printed stickers), may suffe…
Visual Riddles: a Commonsense and World Knowledge Challenge for Large Vision and Language Models
Nitzan Bitton-Guetta, Aviv Slobodkin, Aviya Maimon +6
Imagine observing someone scratching their arm; to understand why, additional context would be necessary. However, spotting a mosquito nearby would immediately offer a likely expla…
DeSparsify: Adversarial Attack Against Token Sparsification Mechanisms in Vision Transformers
Oryan Yehezkel, Alon Zolfi, Amit Baras +2
Vision transformers have contributed greatly to advancements in the computer vision domain, demonstrating state-of-the-art performance in diverse tasks (e.g., image classification,…
QuantAttack: Exploiting Dynamic Quantization to Attack Vision Transformers
Amit Baras, Alon Zolfi, Yuval Elovici +1
In recent years, there has been a significant trend in deep neural networks (DNNs), particularly transformer-based models, of developing ever-larger and more capable models. While…