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Found 3 papers, 1 papers with code
Dynamic Adapter Meets Prompt Tuning: Parameter-Efficient Transfer Learning for Point Cloud Analysis
To achieve this goal, we freeze the parameters of the default pre-trained models and then propose the Dynamic Adapter, which generates a dynamic scale for each token, considering the token significance to the downstream task.
ESTISR: Adapting Efficient Scene Text Image Super-resolution for Real-Scenes
While scene text image super-resolution (STISR) has yielded remarkable improvements in accurately recognizing scene text, prior methodologies have placed excessive emphasis on optimizing performance, rather than paying due attention to efficiency - a crucial factor in ensuring deployment of the STISR-STR pipeline.
Adaptive Multi-User Channel Estimation Based on Contrastive Feature Learning
The similar features will be fed into the downstream network to explore the strong correlations among CSI features to improve the MUCE performance with a small number of labeled data.
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