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Found 11 papers, 1 papers with code
Optical Lens Attack on Monocular Depth Estimation for Autonomous Driving
Monocular Depth Estimation (MDE) is a pivotal component of vision-based Autonomous Driving (AD) systems, enabling vehicles to estimate the depth of surrounding objects using a single camera image.
Decoding Emotions: Unveiling Facial Expressions through Acoustic Sensing with Contrastive Attention
Expression recognition holds great promise for applications such as content recommendation and mental healthcare by accurately detecting users' emotional states.
Transient Adversarial 3D Projection Attacks on Object Detection in Autonomous Driving
In this paper, we introduce an adversarial 3D projection attack specifically targeting object detection in autonomous driving scenarios.
Optical Lens Attack on Deep Learning Based Monocular Depth Estimation
The results highlight the significant impact of LensAttack on the accuracy of depth estimation in AD systems.
Protecting Activity Sensing Data Privacy Using Hierarchical Information Dissociation
Hippo achieves fine-grained control over the disclosure of sensitive information without requiring private labels.
MedTrinity-25M: A Large-scale Multimodal Dataset with Multigranular Annotations for Medicine
We then build a comprehensive knowledge base and prompt multimodal large language models to perform retrieval-augmented generation with the identified ROIs as guidance, resulting in multigranular texual descriptions.
Medical Visual Question Answering
Visual Question Answering (VQA)
Beyond Boundaries: A Comprehensive Survey of Transferable Attacks on AI Systems
This survey offers a holistic understanding of the prevailing transferable attacks and their impacts across different domains.
SSVEP-Based BCI Wheelchair Control System
So it demonstrates that this SSVEP-based BCI-controlled wheelchair has a huge potential to be applied to disabled people in the future.
A Comprehensive Survey on Pretrained Foundation Models: A History from BERT to ChatGPT
This study provides a comprehensive review of recent research advancements, challenges, and opportunities for PFMs in text, image, graph, as well as other data modalities.
DoubleStar: Long-Range Attack Towards Depth Estimation based Obstacle Avoidance in Autonomous Systems
By exploiting the weaknesses of the stereo matching in depth estimation algorithms and the lens flare effect in optical imaging, we propose DoubleStar, a long-range attack that injects fake obstacle depth by projecting pure light from two complementary light sources.
Learning Dynamic Siamese Network for Visual Object Tracking
How to effectively learn temporal variation of target appearance, to exclude the interference of cluttered background, while maintaining real-time response, is an essential problem of visual object tracking.
Ranked #5 on
Visual Object Tracking
on OTB-2013
