diff --git a/README.md b/README.md
index aedef40e..6a371bf2 100644
--- a/README.md
+++ b/README.md
@@ -36,11 +36,11 @@ More details: http://pjreddie.com/darknet/yolo/
11. [How to mark bounded boxes of objects and create annotation files](#how-to-mark-bounded-boxes-of-objects-and-create-annotation-files)
12. [How to use Yolo as DLL and SO libraries](#how-to-use-yolo-as-dll-and-so-libraries)
-|  |  mAP@0.5 (AP50) https://pjreddie.com/media/files/papers/YOLOv3.pdf |
+|  |  mAP@0.5 (AP50) https://arxiv.org/abs/1911.11929 https://github.com/WongKinYiu/CrossStagePartialNetworks - more models |
|---|---|
-* YOLOv3-spp better than YOLOv3 - mAP = 60.6%, FPS = 20: https://pjreddie.com/darknet/yolo/
-* Yolo v3 source chart for the RetinaNet on MS COCO got from Table 1 (e): https://arxiv.org/pdf/1708.02002.pdf
+* Yolo v3 on MS COCO: [Speed / Accuracy (mAP@0.5) chart](https://user-images.githubusercontent.com/4096485/52151356-e5d4a380-2683-11e9-9d7d-ac7bc192c477.jpg)
+* Yolo v3 on MS COCO (Yolo v3 vs RetinaNet) - Figure 3: https://arxiv.org/pdf/1804.02767v1.pdf
* Yolo v2 on Pascal VOC 2007: https://hsto.org/files/a24/21e/068/a2421e0689fb43f08584de9d44c2215f.jpg
* Yolo v2 on Pascal VOC 2012 (comp4): https://hsto.org/files/3a6/fdf/b53/3a6fdfb533f34cee9b52bdd9bb0b19d9.jpg
@@ -58,11 +58,23 @@ More details: http://pjreddie.com/darknet/yolo/
There are weights-file for different cfg-files (smaller size -> faster speed & lower accuracy:
-* `yolov3-openimages.cfg` (247 MB COCO **Yolo v3**) - requires 4 GB GPU-RAM: https://pjreddie.com/media/files/yolov3-openimages.weights
-* `yolov3-spp.cfg` (240 MB COCO **Yolo v3**) - requires 4 GB GPU-RAM: https://pjreddie.com/media/files/yolov3-spp.weights
-* `yolov3.cfg` (236 MB COCO **Yolo v3**) - requires 4 GB GPU-RAM: https://pjreddie.com/media/files/yolov3.weights
-* `yolov3-tiny.cfg` (34 MB COCO **Yolo v3 tiny**) - requires 1 GB GPU-RAM: https://pjreddie.com/media/files/yolov3-tiny.weights
-* `enet-coco.cfg` (EfficientNetb0-Yolo- 45.5% mAP@0.5 - 3.7 BFlops) [enetb0-coco_final.weights](https://drive.google.com/file/d/1FlHeQjWEQVJt0ay1PVsiuuMzmtNyv36m/view) and `yolov3-tiny-prn.cfg` (33.1% mAP@0.5 - 3.5 BFlops - [more](https://github.com/WongKinYiu/PartialResidualNetworks))
+* [csresnext50-panet-spp.cfg](https://raw.githubusercontent.com/AlexeyAB/darknet/master/cfg/csresnext50-panet-spp.cfg) - **60.0% mAP@0.5 - 44 FPS** - 71.3 BFlops - 217 MB: [csresnext50-panet-spp_final.weights](https://drive.google.com/file/d/1aNXdM8qVy11nqTcd2oaVB3mf7ckr258-/view?usp=sharing)
+
+* [yolov3-spp.cfg](https://raw.githubusercontent.com/AlexeyAB/darknet/master/cfg/yolov3-spp.cfg) - **60.6% mAP@0.5 - 30 FPS** - 141.5 BFlops - 240 MB: [yolov3-spp.weights](https://pjreddie.com/media/files/yolov3-spp.weights)
+
+* [yolov3-tiny-prn.cfg](https://raw.githubusercontent.com/AlexeyAB/darknet/master/cfg/yolov3-tiny-prn.cfg) - **33.1% mAP@0.5 - 400 FPS** - 3.5 BFlops - 18.8 MB: [yolov3-tiny-prn.weights](https://drive.google.com/file/d/18yYZWyKbo4XSDVyztmsEcF9B_6bxrhUY/view?usp=sharing)
+
+* [enet-coco.cfg (EfficientNetB0-Yolov3)](https://raw.githubusercontent.com/AlexeyAB/darknet/master/cfg/enet-coco.cfg) - **45.5% mAP@0.5 - 60 FPS** - 3.7 BFlops - 18.3 MB: [enetb0-coco_final.weights](https://drive.google.com/file/d/1FlHeQjWEQVJt0ay1PVsiuuMzmtNyv36m/view)
+
+* [yolov3-openimages.cfg](https://raw.githubusercontent.com/AlexeyAB/darknet/master/cfg/yolov3-openimages.cfg) - 247 MB: [yolov3-openimages.weights](https://pjreddie.com/media/files/yolov3-openimages.weights)
+
+CLICK ME - Yolo v3 models
+
+* [yolov3.cfg](https://raw.githubusercontent.com/AlexeyAB/darknet/master/cfg/yolov3.cfg) - **55.3% mAP@0.5 - 46 FPS** - 65.9 BFlops - 236 MB: [yolov3.weights](https://pjreddie.com/media/files/yolov3.weights)
+
+* [yolov3-tiny.cfg](https://raw.githubusercontent.com/AlexeyAB/darknet/master/cfg/yolov3-tiny.cfg) - **33.1% mAP@0.5 - 330 FPS** - 5.6 BFlops - 33.7 MB: [yolov3-tiny.weights](https://pjreddie.com/media/files/yolov3-tiny.weights)
+
+CLICK ME - Yolo v2 models