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Found 4 papers, 3 papers with code
Ship in Sight: Diffusion Models for Ship-Image Super Resolution
In this context, our method explores in depth the problem of ship image super resolution, which is crucial for coastal and port surveillance.
Adaptive Point Transformer
The recent surge in 3D data acquisition has spurred the development of geometric deep learning models for point cloud processing, boosted by the remarkable success of transformers in natural language processing.
MIND: Multi-Task Incremental Network Distillation
The recent surge of pervasive devices that generate dynamic data streams has underscored the necessity for learning systems to adapt continually to data distributional shifts.
DUCK: Distance-based Unlearning via Centroid Kinematics
Machine Unlearning is rising as a new field, driven by the pressing necessity of ensuring privacy in modern artificial intelligence models.
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