5 papers
SABER: Spatially Consistent 3D Universal Adversarial Objects for BEV Detectors
Aixuan Li, Mochu Xiang, Bosen Hou +3
Adversarial robustness of BEV 3D object detectors is critical for autonomous driving (AD). Existing invasive attacks require altering the target vehicle itself (e.g. attaching patc…
Learning Spatial Decay for Vision Transformers
Yuxin Mao, Zhen Qin, Jinxing Zhou +4
Vision Transformers (ViTs) have revolutionized computer vision, yet their self-attention mechanism lacks explicit spatial inductive biases, leading to suboptimal performance on spa…
Autoregressive Image Generation with Linear Complexity: A Spatial-Aware Decay Perspective
Yuxin Mao, Zhen Qin, Jinxing Zhou +6
Autoregressive (AR) models have garnered significant attention in image generation for their ability to effectively capture both local and global structures within visual data. How…
A Generative Victim Model for Segmentation
Aixuan Li, Jing Zhang, Jiawei Shi +2
We find that the well-trained victim models (VMs), against which the attacks are generated, serve as fundamental prerequisites for adversarial attacks, i.e. a segmentation VM is ne…
Generative Edge Detection with Stable Diffusion
Caixia Zhou, Yaping Huang, Mochu Xiang +3
Edge detection is typically viewed as a pixel-level classification problem mainly addressed by discriminative methods. Recently, generative edge detection methods, especially diffu…