LocateAnything with Parallel Box Decoding Turns Visual Grounding Into an Agent Primitive
6 min read
13 hours ago
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How often have you had a problem that requires you to identify what is on the screen, or what is part of the image, or a particular part of the video stream? If you have ever dealt with this problem, one of the biggest problems is the speed of identification. Usually, these identification algorithms are sequential.
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NVIDIA might have just given you something that would solve most of your latency-related headaches. This should open up the door for users to implement agent AI workflows on visually grounded information.
The Problem That Leads To A Misclick
Imagine that you’re trying to tell your parents to click on the start button, go to the menu, type settings, select control panel, and change some settings. You know the headache, you know the difficulty, how it feels. Now imagine the same problem being done by a large language model agentic system.
A desktop agent is trying to click on a button that is deep into the user interface system. The large language models know the instruction to open the settings…