Extending One-Stage Detection with Open-World Proposals. (arXiv:2201.02302v1 [cs.CV])

In many applications, such as autonomous driving, hand manipulation, or robot
navigation, object detection methods must be able to detect objects unseen in
the training set. Open World Detection(OWD) seeks to tackle this problem by
generalizing detection performance to seen and unseen class categories. Recent
works have seen success in the generation of class-agnostic proposals, which we
call Open-World Proposals(OWP), but this comes at the cost of a big drop on the
classification task when both tasks are considered in …

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