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    AgentSTAR reportedly tracks jointed objects through rapid motion and severe occlusion

    A post introducing AgentSTAR describes an agent-based method for reconstructing and tracking jointed objects from single-camera video. It claims tracking can handle rapid motion, objects largely hidden from view and thin objects.

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    TLDR

    The AgentSTAR announcement describes reconstruction and tracking of articulated objects—objects with joints—from monocular, or single-camera, video. It claims the method can track despite rapid motion and severe occlusion, and can handle thin objects. Commentary highlights both the approach’s complexity and its potential: one quote-post calls it “heavyweight but general and effective,” while another argues that AI agents can take on research trial and error, testing techniques and adjusting parameters to reach a desired output.

    Combined views

    105.6K

    5 Sources, first seen 16d ago

    Combined views

    105.6K

    5 Sources, first seen 16d ago

    678 likes
    16d ago
    first seen 16d ago
    678 likes
    10 comments
    497 saves
    96 reposts

    Sentiment

    Positive——Negative

    Summary

    Not enough discussion yet.

    No sentiment analysis available yet.

    10 comments
    497 saves
    96 reposts

    Sentiment

    Positive——Negative

    Summary

    Not enough discussion yet.

    No sentiment analysis available yet.

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    5 Sources

    @makezurAgentSTAR is an agentic method for both reconstruction and tracking of articulated objects from monocular videos. We can now track through rapid motion, severe occlusion and thin objects! There’s no spoon but we can still track it 🥄
    @AjdDavisonHeavyweight but general and effective! Using agents to manage VLAs in a closed loop to model amd track 3D objects accurately in video. From Kirill and co. at Amazon.
    @JitendraMalikCVIn the old days we used to talk about "graduate student descent" or "researcher gradient descent" as referring to the phase in research where one tries various techniques, changes parameters in the hope of getting to some desired output. Now we can get AI agents to do it. The classic CV paradigm of analysis by synthesis becomes considerably more powerful this way.
    @CSProfKGDRT @makezur: AgentSTAR is an agentic method for both reconstruction and tracking of articulated objects from monocular videos. We can now…

    5 Sources

    @makezurAgentSTAR is an agentic method for both reconstruction and tracking of articulated objects from monocular videos. We can now track through rapid motion, severe occlusion and thin objects! There’s no spoon but we can still track it 🥄
    @AjdDavisonHeavyweight but general and effective! Using agents to manage VLAs in a closed loop to model amd track 3D objects accurately in video. From Kirill and co. at Amazon.
    @JitendraMalikCVIn the old days we used to talk about "graduate student descent" or "researcher gradient descent" as referring to the phase in research where one tries various techniques, changes parameters in the hope of getting to some desired output. Now we can get AI agents to do it. The classic CV paradigm of analysis by synthesis becomes considerably more powerful this way.
    @CSProfKGDRT @makezur: AgentSTAR is an agentic method for both reconstruction and tracking of articulated objects from monocular videos. We can now…