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Found 6 papers, 0 papers with code
ControlTraj: Controllable Trajectory Generation with Topology-Constrained Diffusion Model
Generating trajectory data is among promising solutions to addressing privacy concerns, collection costs, and proprietary restrictions usually associated with human mobility analyses.
Copyleft for Alleviating AIGC Copyright Dilemma: What-if Analysis, Public Perception and Implications
As AIGC has impacted our society profoundly in the past years, ethical issues have received tremendous attention.
Towards Function Space Mesh Watermarking: Protecting the Copyright of Signed Distance Fields
Our method can recover the message with high-resolution meshes extracted from SDFs and detect the watermark even when mesh vertices are extremely sparse.
CopyScope: Model-level Copyright Infringement Quantification in the Diffusion Workflow
Previous work only focused on data attribution from the training data perspective, which is unsuitable for tracing and quantifying copyright infringement in practice because of the following reasons: (1) the training datasets are not always available in public; (2) the model provider is the responsible party, not the image.
EFFL: Egalitarian Fairness in Federated Learning for Mitigating Matthew Effect
Recent advances in federated learning (FL) enable collaborative training of machine learning (ML) models from large-scale and widely dispersed clients while protecting their privacy.
Deep Boosting Robustness of DNN-based Image Watermarking via DBMark
In this paper, we propose DBMARK, a novel end-to-end digital image watermarking framework to deep boost the robustness of DNN-based image watermarking.
