One of the biggest bottlenecks in deploying visual AI and computer vision is annotation, which can be both costly and time-consuming. Today, weโre introducing Verified Auto Labeling, a new approach to AI-assisted annotation that achieves up to 95% of human-level performance while cutting labeling costs by up to 100,000x and time by 5,000x.
Read the full paper: https://t.co/eKc1sALnV3
๐ Excited to share our new paper "Learning to Describe Scenes via Privacy-aware Designed Optical Lens" in @IEEE_TCI@PaulisArguello, @Jhon__98__, @CarlosH_93, @henarfu
๐๐ธ Paper link: https://t.co/4pvuNv19jY
We protect visual privacy while maintaining the task utility.