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Found 2 papers, 2 papers with code
DiGeo: Discriminative Geometry-Aware Learning for Generalized Few-Shot Object Detection
Generalized few-shot object detection aims to achieve precise detection on both base classes with abundant annotations and novel classes with limited training data.
Revisiting 3D Context Modeling with Supervised Pre-training for Universal Lesion Detection in CT Slices
We demonstrate that with the novel pre-training method, the proposed MP3D FPN achieves state-of-the-art detection performance on the DeepLesion dataset (3. 48% absolute improvement in the sensitivity of FPs@0. 5), significantly surpassing the baseline method by up to 6. 06% (in MAP@0. 5) which adopts 2D convolution for 3D context modeling.
Ranked #4 on
Medical Object Detection
on DeepLesion
