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Found 2 papers, 2 papers with code
Motion Style Transfer: Modular Low-Rank Adaptation for Deep Motion Forecasting
To this end, we introduce two components that exploit our prior knowledge of motion style shifts: (i) a low-rank motion style adapter that projects and adjusts the style features at a low-dimensional bottleneck; and (ii) a modular adapter strategy that disentangles the features of scene context and motion history to facilitate a fine-grained choice of adaptation layers.
Using Machine Learning to generate an open-access cropland map from satellite images time series in the Indian Himalayan Region
To this end, we developed an ML pipeline that relies on Sentinel-2 satellite images time series.
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