Stock and Archive Footage for AI Video

Stock and archive footage is real, previously shot video that a production licenses or reuses rather than filming or generating itself. It matters more in AI video than it might seem. Not every shot needs to come from a generative model: a city at night, a 1950s kitchen or a rocket launch may already exist on film, and using it avoids generation costs and the questions that come with synthetic shots. Agent pipelines now search these sources automatically. The footage comes from three kinds of place, royalty-free libraries, public-domain and government archives, and Creative Commons collections, and each one has license terms the pipeline has to track.

Royalty-Free Libraries

Pexels and Pixabay are two of the best-known free libraries of stock photos and video, and both offer free developer API keys, which makes them easy for AI tools to search. Both joined the design company Canva in May 2019. Each now publishes its own license:

• The Pexels License makes all photos and videos free to use, without attribution, and allows modification. It forbids showing identifiable people in a bad light, selling unaltered copies, implying that people or brands in the footage endorse a product, and redistributing the media on other stock or wallpaper sites.
• The Pixabay Content License is similar: free use and adaptation without attribution, but no selling or distributing content on a standalone basis, no misleading use, and no commercial use of content that contains recognizable trademarks, logos or brands.

Unsplash offers free stock photographs, and smaller libraries such as Coverr, Mixkit and Videvo focus on video. Paid libraries such as Getty Images and Shutterstock license footage under commercial terms rather than free licenses; see Getty Images vs Shutterstock.

Public-Domain and Government Archives

• The Prelinger Archives. Founded by Rick Prelinger in 1982, the collection of industrial, educational, advertising and amateur films transferred its physical films to the Library of Congress in 2002. More than 8,500 public-domain films from it are on the Internet Archive for unrestricted reuse. They are the classic source for archival montage.
• NASA. NASA images and video are generally not subject to copyright in the United States, and NASA asks to be credited as the source. Uses must not imply NASA's endorsement, its insignia and logos are protected by law, identifiable people need to give permission for commercial uses, and third-party material that NASA publishes is marked with its own copyright holder.
• Wikimedia Commons. Commons accepts only freely licensed or public-domain media, including CC0, CC BY and CC BY-SA, and refuses non-commercial and no-derivatives licenses. Reusers are responsible for following each file's license, which often means attribution and, for share-alike files, licensing adaptations the same way (see Creative Commons).
• Other agencies. The Library of Congress, the National Archives, NOAA, ESA and JAXA all publish footage, on terms that differ by agency and item. Agencies outside the US government, such as ESA and JAXA, set their own rules.

License Traps

• Royalty-free is not rights-free. A license covers the copyright in the footage, not the people, brands, artworks or music it shows. Pixabay bars commercial use of footage with recognizable trademarks, Pexels bars implied endorsement, and NASA warns that commercial use of a person's image may infringe their right of publicity.
• Public domain is item by item. Archives mix public-domain and copyrighted works, and public-domain status can differ between countries, so each clip's status needs checking rather than assuming it from the collection.
• Attribution and share-alike. Pexels and Pixabay don't require credit, but CC BY and CC BY-SA files do, and NASA asks for it. A pipeline that mixes sources has to carry each clip's terms through to the credits.
• Redistribution. Free licenses allow footage inside a finished work, not repackaging it as stock.
• Disclosure. When real and generated shots are cut together, viewers may not be able to tell which is which, and labeling rules and platform policies increasingly expect generated content to be disclosed (see AI content labeling and C2PA).

The practical answer is provenance: record where every clip came from, its original URL and its license. OpenMontage's documentary-montage pipeline, for example, will not count an edit as successful unless every asset carries its provider, original URL and license.

How Agents Find Footage

Keyword search through library APIs is the simplest method, but stock metadata is thin and inconsistent. Semantic retrieval works better. CLIP, a model published by OpenAI in 2021, maps images and text into the same space, so a shot description such as "rain on a bus window at night" can be compared directly with frames from thousands of clips (see embeddings and semantic search). A pipeline samples frames from each candidate clip, embeds them, and picks the nearest match for every slot in the script. OpenMontage builds its documentary-montage corpus this way from Archive.org, NASA, Wikimedia Commons, Pexels and Unsplash, fills each slot with exactly one clip, never uses a clip twice, and applies one color grade across footage from different eras. Richer video understanding models extend the same idea from single frames to motion and sound.

Stock and archive footage and generation increasingly work together. A pipeline can search the archives first and generate only the shots that do not exist, which lowers cost and keeps generated material to the places where it is needed. For the wider production picture, see AI filmmaking.