/LandmarkConv

Efficient Convolutional Module for Semantic Understanding

Primary LanguageCuda

LandmarkConv

Efficient Convolutional Module for Semantic Understanding

This work is an extended version for the convolutional module in LBYL-Net

  • Operator for general semantic understanding tasks like semantic segmentation and visual grounding

  • Easily being inserted into layers

  • Efficient computational process with linear space and time