Whos.tv is an AI-driven AV video scene search and content discovery platform. We are committed to allowing users to explore the AV world in a more direct and efficient way, helping users quickly find their favorite AV videos and actresses through image recognition, face recognition, tag systems, and intelligent recommendations.
Whos.tv hopes to become the world's leading adult movie search engine and tag database, allowing users to no longer rely on titles or keywords, but to let machines directly understand images, characters, and emotions.
In the future, we hope to build on the platform:
What Whos.tv wants to do is to make AV videos searchable, organizable, and reconstructible.
Users upload a screenshot to automatically match the video source, time location, and similar scenes.
Relying on deep visual models, we have achieved millisecond-level scene vector search, making images the key to indexing the AV world.
We have built a constantly updating actress recognition system that supports facial feature analysis, similarity matching, work aggregation, and profile display.
Understanding images better, and understanding people better.
The platform is building a structured scene tag network, including: various AV famous scenes and actress catalogs.
Users can browse relevant selected scenes under any tag, forming a themed visual experience.
The birth of Whos.tv comes from a resistance to the "information overload era".
When there is more and more video content, ordinary search methods can no longer meet user needs.
Inaccurate titles, chaotic tags, and fragmented information make "finding a picture" an extremely difficult task.
We want to change this.
So we started training models, building databases, and setting up tag systems, trying to do something not simple but meaningful:
Let images find their belonging, and let users find that second, that moment they want.
Whos.tv will continue to improve:
We hope Whos.tv is not just a platform, but a new way of viewing.
Whos.tv is an AI-powered AV video scene search and content discovery platform. We are committed to providing users with a more direct and efficient way to explore the AV world, helping them quickly find their favorite AV videos and actresses through image recognition, face recognition, tag systems, and intelligent recommendations.
