Widely Used Computer Vision Tests Flawed says MIT

[RoboGuy]

Computer vision may not be making as much progress as recent research results seem to suggest, a new MIT study says. The new study, "Why is Real-World Visial Object Recognition Hard?" (PDF format), was written by MIT researchers Nicolas Pinto, David D. Cox, and James J. DiCarlo of MIT's DiCarlo Lab. Commonly used computer vision testing methods may actually be making things worse, say the researchers: "these results demonstrate that tests based on uncontrolled natural images can be seriously misleading, potentially guiding progress in the wrong direction." The researchers offer suggestions for types of images that should be used to test computer vision progress and call for "a renewed focus on the core problem of object recognition—real-world image variation." For more, see the MIT News summary of their paper.

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