Hier-DETR reports state-of-the-art incremental detection accuracy, 48.4 AP on COCO 70+10 and 45.46 AP on MTSD 150+71, using a frozen hierarchical tree of general orthogonal frame prototypes with a proxy-based guiding loss.
In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
baseline 1
citation-polarity summary
fields
cs.CV 1years
2025 1verdicts
CONDITIONAL 1roles
baseline 1polarities
baseline 1representative citing papers
citing papers explorer
-
Hierarchical Neural Collapse Detection Transformer for Class Incremental Object Detection
Hier-DETR reports state-of-the-art incremental detection accuracy, 48.4 AP on COCO 70+10 and 45.46 AP on MTSD 150+71, using a frozen hierarchical tree of general orthogonal frame prototypes with a proxy-based guiding loss.