SimpleDet: A Simple and Versatile Distributed Framework for Object Detection and Instance Recognition

Naiyan Wang

Abstract:

Object detection and instance recognition play a central role in many AI applications like
autonomous driving, video surveillance and medical image analysis. However, training object detection models on large scale datasets remains computationally expensive and time
consuming. This paper presents an efficient and open source object detection framework
called SimpleDet which enables the training of state-of-the-art detection models on consumer grade hardware at large scale. SimpleDet covers a wide range of models including
both high-performance and high-speed ones. SimpleDet is well-optimized for both low precision training and distributed training and achieves 70% higher throughput for the Mask
R-CNN detector compared with existing frameworks. Codes, examples and documents of
SimpleDet can be found at https://github.com/tusimple/simpledet.