calls nanodet “Ultra-lightweight anchor-free detector, choose for mobile/edge deployment.”
OpenMMLab Detection Toolbox and Benchmark
nanodet 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 nanodet among their alternatives. The relationship is not symmetric — how nanodet rates them is a separate judgement, made when nanodet is analysed in its own right.
calls nanodet “Ultra-lightweight anchor-free detector, choose for mobile/edge deployment.”
OpenMMLab Detection Toolbox and Benchmark
calls nanodet “Use when you need a super-lightweight anchor-free detector for on-device deployment instead of learning from a tutorial.”
deep learning for image processing including classification and object-detection etc.
calls nanodet “choose for a single ultra-lightweight mobile anchor-free detector, but it is narrower and unmaintained.”
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 nanodet “Ultra-lightweight anchor-free detector — choose for mobile/edge deployment where PaddleDetection models are too heavy.”
Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.