Visual Turing Test Visual Turing Test Computer vision research is driven by standard evaluation practices. The current systems are tested by their accuracy for tasks like object detection, segmentation and localization. Methods like the convolutional neural networks seem to be doing pretty well in these tasks, but the current systems are still not close to solving the ultimate problem of understanding images the way humans do. So motivated by the ability of humans to understand an image and even tell a story about it, Geman "et al." have introduced the Visual Turing Test for computer vision systems. As described in, it is “an
Reverse Turing test much shared ground between the skill of the reverse Turing test and the skill of mentally simulating a program's operation in the course of computer programming and especially debugging. As a result, programmers (especially hackers) will sometimes indulge in an informal reverse Turing test for recreation. An informal reverse Turing test involves an attempt to simulate a computer without the formal structure of the Turing test. The judges of the test are typically not aware in advance that a reverse Turing test is occurring, and the test subject attempts to elicit from the 'judges' (who, correctly, think they are speaking