Sparse Visual Prompt for Efficient Domain Adaptation in Dense Prediction Tasks

A novel Sparse Visual Domain Prompt (SVDP) approach that applies minimal trainable parameters to pixels across the entire image, reserving more spatial information to better extract local domain knowledge and transfer pixel-wise data distribution from source to target domain.