deep_learning_object_detection

Why we included this project

Tracing how object detection evolved is usually a long slog through arxiv, and this paper list spares you most of it. The author organized the major detection papers year by year from 2014 through 2020, with each entry linking to the PDF and, where it exists, official or community code. A companion performance table puts dozens of detectors side by side on VOC and COCO, which makes it easy to see which architecture reported what mAP at a glance, and a history diagram plus a dedicated dataset-papers section round out the package. The honest caveat is that maintenance stopped around late 2020, so treat it as a strong historical foundation and pair it with newer work for current coverage.