From 3da005b3bf12ff03d526eed7f74c6e55e1ec85cd Mon Sep 17 00:00:00 2001
From: Jon Almazan <jon@v7labs.com>
Date: Thu, 5 Sep 2019 18:24:37 +0100
Subject: [PATCH] update mAP numbers

---
 README.md | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/README.md b/README.md
index 47b30e5..27f5296 100644
--- a/README.md
+++ b/README.md
@@ -59,11 +59,11 @@ The table below contains the pre-trained models that we provide with this librar
 
 | Model | Oxford5K | Paris6K |  ROxford5K (med/hard) | RParis6K (med/hard) |
 |---	|:-:|:-:|:-:|:-:|
-|  [Resnet101-TL-MAC](https://drive.google.com/file/d/13MUGNwn_CYGZvqDBD8FGD8fVYxThsSDg/view?usp=sharing) |  84.2 	|  91.0| 63.6 / 37.1 	|   76.7 / 55.7  |
-|  [Resnet101-TL-GeM](https://drive.google.com/open?id=1vhm1GYvn8T3-1C4SPjPNJOuTU9UxKAG6) | 85.5 | 93.4 | 64.8 / 41.6	|  78.9 / 59.4  |
-|  [Resnet50-AP-GeM](https://drive.google.com/file/d/1oPtE_go9tnsiDLkWjN4NMpKjh-_md1G5/view?usp=sharing) | 87.9 	| 91.9 | 65.8 / 41.7| 77.6 / 57.3 |
-|  [Resnet101-AP-GeM](https://drive.google.com/open?id=1UWJGDuHtzaQdFhSMojoYVQjmCXhIwVvy) | **89.3** | **93.0** | **67.4** / 42.8|  **80.4**/**61.0** |
-|  [Resnet101-AP-GeM-LM18](https://drive.google.com/open?id=1r76NLHtJsH-Ybfda4aLkUIoW3EEsi25I)** |  88.4	| **93.0** | 66.5 / **43.1**	|   80.2 / 60.4  |
+|  [Resnet101-TL-MAC](https://drive.google.com/file/d/13MUGNwn_CYGZvqDBD8FGD8fVYxThsSDg/view?usp=sharing) |  85.6	| 90.1 |  63.3 / 35.7 	|   76.6 / 55.5  |
+|  [Resnet101-TL-GeM](https://drive.google.com/open?id=1vhm1GYvn8T3-1C4SPjPNJOuTU9UxKAG6) | 85.7 | **93.4** | 64.5 / 40.9 |  78.8 / 59.2  |
+|  [Resnet50-AP-GeM](https://drive.google.com/file/d/1oPtE_go9tnsiDLkWjN4NMpKjh-_md1G5/view?usp=sharing) | 87.7 	| 91.9 |  65.5 / 41.0 | 77.6 / 57.1 |
+|  [Resnet101-AP-GeM](https://drive.google.com/open?id=1UWJGDuHtzaQdFhSMojoYVQjmCXhIwVvy) | **89.1** | **93.0** | **67.1** / **42.3** |  **80.3**/**60.9** |
+|  [Resnet101-AP-GeM-LM18](https://drive.google.com/open?id=1r76NLHtJsH-Ybfda4aLkUIoW3EEsi25I)** |  88.1	| **93.1** | 66.3 / **42.5**	|   **80.2** / **60.8**  |
 
 
 The name of the model encodes the backbone architecture of the network and the loss that has been used to train it (TL for triplet loss and AP for Average Precision loss). All models use **Generalized-mean pooling (GeM)** [3] as the global pooling mechanism, except for the model in the first row that uses MAC [3] \(i.e. max-pooling), and have been trained on the **Landmarks-clean** [1] dataset (the clean version of the [Landmarks dataset](http://sites.skoltech.ru/compvision/projects/neuralcodes/)) directly **fine-tuning from ImageNet**. These numbers have been obtained using a **single resolution** and applying **whitening** to the output features (which has also been learned on Landmarks-clean). For a detailed explanation of all the hyper-parameters see [1] and [2] for the triplet loss and AP loss models, respectively.
-- 
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