50 citations · 73 across the 2 of their papers we have counts for
8 papers · 1 filter
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…
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…
Joint Salient Object Detection and Camouflaged Object Detection via Uncertainty-aware Learning
Aixuan Li, Jing Zhang, Yunqiu Lv +4
Salient objects attract human attention and usually stand out clearly from their surroundings. In contrast, camouflaged objects share similar colors or textures with the environmen…
Mutual Information Regularization for Weakly-supervised RGB-D Salient Object Detection
Aixuan Li, Yuxin Mao, Jing Zhang +1
In this paper, we present a weakly-supervised RGB-D salient object detection model via scribble supervision. Specifically, as a multimodal learning task, we focus on effective mult…
Fine-grained Audible Video Description
Xuyang Shen, Dong Li, Jinxing Zhou +9
We explore a new task for audio-visual-language modeling called fine-grained audible video description (FAVD). It aims to provide detailed textual descriptions for the given audibl…
Simultaneously Localize, Segment and Rank the Camouflaged Objects
Yunqiu Lv, Jing Zhang, Yuchao Dai +4
Camouflage is a key defence mechanism across species that is critical to survival. Common strategies for camouflage include background matching, imitating the color and pattern of…