diff --git a/README.md b/README.md index 1c9198aa..6ae33772 100644 --- a/README.md +++ b/README.md @@ -216,6 +216,15 @@ If you find this implementation or the analysis conducted in our report helpful, Journal = {arXiv preprint arXiv:1702.02138}, Year = {2017} } + +Or for a formal paper, [Spatial Memory Network](https://arxiv.org/abs/1704.04224): + + @article{chen2017spatial, + title={Spatial Memory for Context Reasoning in Object Detection}, + author={Chen, Xinlei and Gupta, Abhinav}, + journal={arXiv preprint arXiv:1704.04224}, + year={2017} + } For convenience, here is the faster RCNN citation: @@ -226,39 +235,3 @@ For convenience, here is the faster RCNN citation: Booktitle = {Advances in Neural Information Processing Systems ({NIPS})}, Year = {2015} } - -### Detailed numbers from COCO server (Needs to be updated) - -All the models are trained on COCO 2014 [trainval35k](https://github.com/rbgirshick/py-faster-rcnn/tree/master/models). - -VGG16 COCO 2015 test-dev (900k/1190k): -``` - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.297 - Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.504 - Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.312 - Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.128 - Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.325 - Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.421 - Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.272 - Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.399 - Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.409 - Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.187 - Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.451 - Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.591 - ``` - -VGG16 COCO 2015 test-std (900k/1190k): - ``` - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.295 - Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.501 - Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.312 - Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.119 - Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.327 - Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.418 - Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.273 - Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.400 - Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.409 - Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.179 - Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.455 - Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.586 - ```