CFGPatch combines curved fractal geometry with modality-specific spiral textures to create adversarial patches that fool VIS-IR VLMs and transfer across classification, captioning, and VQA tasks.
Learning transferable visual models from natural language supervision
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
fields
cs.CV 3years
2026 3verdicts
UNVERDICTED 3representative citing papers
GuardMarkGS unifies watermarking and adversarial edit deterrence into a single optimization framework for protecting 3D Gaussian Splatting assets.
SpecSem-Net integrates Fourier-based spectral filtering with semantic-guided gated merging to detect AI-generated videos, reporting 87.25% accuracy on a new benchmark of five commercial generators and 95.59% on public datasets.
citing papers explorer
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Exposing Vulnerabilities in Visible-Infrared VLMs: A Unified Geometric Adversarial Framework with Cross-Task Transferability
CFGPatch combines curved fractal geometry with modality-specific spiral textures to create adversarial patches that fool VIS-IR VLMs and transfer across classification, captioning, and VQA tasks.
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GuardMarkGS: Unified Ownership Tracing and Edit Deterrence for 3D Gaussian Splatting
GuardMarkGS unifies watermarking and adversarial edit deterrence into a single optimization framework for protecting 3D Gaussian Splatting assets.
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SpecSem-Net: Integrating Spectral and Semantic Features for Robust AI-generated Video Detection
SpecSem-Net integrates Fourier-based spectral filtering with semantic-guided gated merging to detect AI-generated videos, reporting 87.25% accuracy on a new benchmark of five commercial generators and 95.59% on public datasets.