Detect unknown and known objects using image semantics and slots with OpenSlot
Detect unknown and known objects using image semantics and slots with OpenSlot
OpenSlot: Mixed Open-set Recognition with Object-centric Learning
arXiv paper abstract https://arxiv.org/abs/2407.02386
arXiv PDF paper https://arxiv.org/pdf/2407.02386
... open-set recognition (OSR) ... assume ... image contains only one ... label, and the unknown test set (negative) has a disjoint label space from the known test set (positive) ...
... introduces the mixed OSR problem, where test images contain multiple class semantics, with known and unknown classes co-occurring in negatives
... propose the OpenSlot framework, built upon object-centric learning. OpenSlot utilizes slot features to represent diverse class semantics and produce class predictions.
... anti-noise-slot (ANS) ... mitigate the ... noise (invalid and background) slots during ... training, ... addressing ... misalignment between ... predictions and the ground truth.
... OpenSlot ... exceeds existing OSR studies in detecting super-label shifts across single & multi-label mixed OSR tasks ... achieves state-of-the-art performance on ... benchmarks.
Remarkably, ... method can localize class objects without using bounding boxes during training ...
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