6 DAILY WACV Monday Oral Presentation a selective coarse-to-fine decoder approach: first examining the expanded area at low resolution, then refining only the most promising candidate regions. The result is a lightweight detector that can run at around three to five frames per second. “Basically, you can do it in real time,” Changlin adds. “I guess that’s the biggest value that we’re exploring.” For Changlin, the significance of the work goes beyond performance metrics. “The ultimate goal of computer vision is to make the machine look like a human,” he says. As humans, we do not assume objects vanish when they move beyond our immediate view. We infer their continued presence. “By equipping the machine learning models with this ability, we can make them more reliable, more powerful, and more like a human.”
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