RoI Feature Extractors

RoIAlign

Introduced by He et al. in Mask R-CNN

Region of Interest Align, or RoIAlign, is an operation for extracting a small feature map from each RoI in detection and segmentation based tasks. It removes the harsh quantization of RoI Pool, properly aligning the extracted features with the input. To avoid any quantization of the RoI boundaries or bins (using $x/16$ instead of $[x/16]$), RoIAlign uses bilinear interpolation to compute the exact values of the input features at four regularly sampled locations in each RoI bin, and the result is then aggregated (using max or average).

Source: Mask R-CNN

Papers


Paper Code Results Date Stars

Tasks


Task Papers Share
Semantic Segmentation 194 16.99%
Instance Segmentation 173 15.15%
Object Detection 149 13.05%
Image Classification 25 2.19%
General Classification 19 1.66%
Pose Estimation 16 1.40%
Classification 15 1.31%
Panoptic Segmentation 15 1.31%
Image Segmentation 13 1.14%

Components


Component Type
🤖 No Components Found You can add them if they exist; e.g. Mask R-CNN uses RoIAlign

Categories