calls simpledet “Choose if your stack is MXNet and you need a framework covering detection and instance recognition, not PyTorch.”
Mask R-CNN for object detection and instance segmentation on Pytorch
simpledet is queued for analysis. Crawling candidates and ranking them takes a few minutes. This page updates itself when the list exists — you can also come back later.
What is known so far comes from the other direction:
These projects were analysed and named simpledet among their alternatives. The relationship is not symmetric — how simpledet rates them is a separate judgement, made when simpledet is analysed in its own right.
calls simpledet “Choose if your stack is MXNet and you need a framework covering detection and instance recognition, not PyTorch.”
Mask R-CNN for object detection and instance segmentation on Pytorch
calls simpledet “Older, simple object detection framework; use if you need its legacy codebase.”
deep learning for image processing including classification and object-detection etc.
calls simpledet “Previous-generation lightweight detection/segmentation framework; choose if you need a simpler API, but it is stale and limited.”
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
calls simpledet “choose for a simple older detection framework as a baseline, but stale and narrower.”
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
calls simpledet “Choose for a legacy framework implementation of instance segmentation if you're on older infrastructure.”
SOLO and SOLOv2 for instance segmentation, ECCV 2020 & NeurIPS 2020.