In the summer of 2020, CAMPI (the Computer-Aided Metadata Generation for Photoarchvies Initiative) assessed the use of computer vision in assisting in the arduous task of processing digital photograph collections. The prototype built to find duplicates and tag photos depicting similar scenes in Carnegie Mellon University Archives’ General Photography Collection was successful, proving such an interface would be both feasible and useful for cultural heritage institutions with large visual collections.This whitepaper reports on the background for this project, the specific tasks, methods, and results from our software prototype, and a summary of future directions and needs for both computer vision as well as interfaces for photo archive description. We also offer a high-level technical roadmap as well as specific implementation details and reference code for our prototype.