MIT News  December 10, 2019 In the real-world object detectors’ performance drops noticeably creating reliability concerns for self-driving cars and other safety-critical systems that use machine vision. A team of researchers (MIT, IBM) created ObjectNet consisting of about 50,000 photos of objects shown tipped on their side, shot at odd angles, and displayed in clutter-strewn rooms and it contains no training images. When leading object-detection models were tested on ObjectNet, their accuracy rates fell from a high of 97 percent on ImageNet to just 50-55 percent. The researchers hope that the new dataset will result in robust computer vision without […]