ENet Dilated Bottleneck

Introduced by Paszke et al. in ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation

ENet Dilated Bottleneck is an image model block used in the ENet semantic segmentation architecture. It is the same as a regular ENet Bottleneck but employs dilated convolutions instead.

Source: ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation

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Papers

Paper	Code	Results	Date	Stars

Tasks

Task	Papers	Share
Semantic Segmentation	12	26.09%
Autonomous Driving	5	10.87%
Quantization	2	4.35%
Autonomous Vehicles	2	4.35%
Real-Time Semantic Segmentation	2	4.35%
Instance Segmentation	2	4.35%
Scene Understanding	2	4.35%
Optical Character Recognition (OCR)	1	2.17%
Multi-Task Learning	1	2.17%

Usage Over Time

This feature is experimental; we are continuously improving our matching algorithm.

Components

Component	Type	Add Remove
1x1 Convolution	Convolutions
Batch Normalization	Normalization
Dilated Convolution	Convolutions
Max Pooling	Pooling Operations
PReLU	Activation Functions
SpatialDropout	Regularization

Categories

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Image Model Blocks