Feature Extractors

Receptive Field Block

Introduced by Liu et al. in Receptive Field Block Net for Accurate and Fast Object Detection

Receptive Field Block (RFB) is a module for strengthening the deep features learned from lightweight CNN models so that they can contribute to fast and accurate detectors. Specifically, RFB makes use of multi-branch pooling with varying kernels corresponding to RFs of different sizes, applies dilated convolution layers to control their eccentricities, and reshapes them to generate final representation.

Source: Receptive Field Block Net for Accurate and Fast Object Detection

Papers


Paper Code Results Date Stars

Tasks


Task Papers Share
Object Detection 3 33.33%
Real-Time Object Detection 2 22.22%
Image Super-Resolution 1 11.11%
Super-Resolution 1 11.11%
Semantic Segmentation 1 11.11%
Clustering 1 11.11%

Categories