BadVSFM is the first effective backdoor attack on prompt-driven video segmentation foundation models, using a two-stage encoder-decoder strategy to achieve high attack success rates with limited clean performance loss.
Importance-aware image segmentation-based semantic communication for autonomous driving,
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FAJSCC is a new deepJSCC architecture for images that achieves better transmission performance with lower complexity than prior models and enables independent encoder-decoder compute adjustment.
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Backdoor Attacks on Prompt-Driven Video Segmentation Foundation Models
BadVSFM is the first effective backdoor attack on prompt-driven video segmentation foundation models, using a two-stage encoder-decoder strategy to achieve high attack success rates with limited clean performance loss.
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Feature Importance-Aware Deep Joint Source-Channel Coding for Computationally Efficient and Adjustable Image Transmission
FAJSCC is a new deepJSCC architecture for images that achieves better transmission performance with lower complexity than prior models and enables independent encoder-decoder compute adjustment.