View Adaptation

View adaptation in computer vision focuses on transferring knowledge learned from one viewpoint (e.g., a single camera, a specific perspective) to another, overcoming limitations of data scarcity or computational constraints in the target view. Current research emphasizes efficient adaptation techniques, often employing lightweight adapter networks or prompt-based methods to modify pre-trained models, minimizing computational overhead while maintaining accuracy. This research is crucial for advancing applications like egocentric vision, multi-view 3D reconstruction, and cross-domain scene understanding, where data from different viewpoints are often available in disparate quantities or formats.