Rabbat said Gfycat will scour the web for the original version of a video where the GIF is coming from — in some cases it comes from YouTube — and analyze that video to figure out what part of it the GIF came from. The company then produces a higher-quality GIF and swaps it out, making the broader spread of the GIF a higher-quality version. The company creates a kind of model for each frame in the GIF and then tries to match that up with the higher-quality videos, he said.
Finally, with all these tools, Gfycat wants to identify text within various captions in GIFs as they come in. Again, part of the challenge here was that a GIF might come in with a caption, but the text is grainy and not easily read or identifiable. Gfycat sought to build some internal tools that help understand what the captions say and then make the GIFs more discoverable based on those captions.
