Apr 3, 2021 · We propose Recursively Refined R-CNN (R^3-CNN) which avoids duplicates by introducing a loop mechanism instead. At the same time, it achieves a quality boost.

Oct 31, 2021 · We propose Recursively Refined R-CNN ( -CNN) which avoids duplicates by introducing a loop mechanism instead. At the same time, it achieves a quality boost ...

At the same time, it achieves a quality boost using a recursive re-sampling technique, where a specific IoU quality is utilized in each recursion to eventually ...

This work proposes Recursively Refined R-CNN (R^3-CNN) which avoids duplicates by introducing a loop mechanism instead, and achieves a quality boost using a ...

At the same time, it achieves a quality boost using a recursive re-sampling technique, where a specific IoU quality is utilized in each recursion to eventually ...

At the same time, it achieves a quality boost using a recursive re-sampling technique, where a specific IoU quality is utilized in each recursion to eventually ...

R3-CNN (ResNet-50-FPN, GC-Net). 56. Recursively Refined R-CNN: Instance Segmentation with Self-RoI Rebalancing. 2021. MS COCO (Microsoft Common Objects in ...

Apr 25, 2024 · A better performing GRoIE model is proposed for extraction of RoIs in a two-stage instance segmentation and object detection architecture.

Recursively refined R-CNN: Instance segmentation with self-roi rebalancing. RossiL. et al. A novel region of interest extraction layer for instance segmentation.

GroIE is an RoI extractor which intends to overcome the limitation of existing extractors which select only one (the best) layer from the FPN.