Merge pull request #1608 from sguada/added_credits

Add credits for training BVLC Models

docs/model_zoo.md

@@ -15,9 +15,10 @@ To lower the friction of sharing these models, we introduce the model zoo framew
 First of all, we provide some trained models out of the box.
 Each one of these can be downloaded by running `scripts/download_model_binary.py <dirname>` where `<dirname>` is specified below:
 
-- **BVLC Reference CaffeNet** in `models/bvlc_reference_caffenet`: AlexNet trained on ILSVRC 2012, with a minor variation from the version as described in the NIPS 2012 paper.
-- **BVLC AlexNet** in `models/bvlc_alexnet`: AlexNet trained on ILSVRC 2012, almost exactly as described in NIPS 2012.
-- **BVLC Reference R-CNN ILSVRC-2013** in `models/bvlc_reference_rcnn_ilsvrc13`: pure Caffe implementation of [R-CNN](https://github.com/rbgirshick/rcnn).
+- **BVLC Reference CaffeNet** in `models/bvlc_reference_caffenet`: AlexNet trained on ILSVRC 2012, with a minor variation from the version as described in the NIPS 2012 paper. (Trained by Jeff Donahue @jeffdonahue)
+- **BVLC AlexNet** in `models/bvlc_alexnet`: AlexNet trained on ILSVRC 2012, almost exactly as described in NIPS 2012. (Trained by Evan Shelhamer @shelhamer)
+- **BVLC Reference R-CNN ILSVRC-2013** in `models/bvlc_reference_rcnn_ilsvrc13`: pure Caffe implementation of [R-CNN](https://github.com/rbgirshick/rcnn). (Trained by Ross Girshick @rbgirshick)
+- **BVLC GoogleNet** in `models/bvlc_googlenet`: GoogleNet trained on ILSVRC 2012, almost exactly as described in [GoogleNet](http://arxiv.org/abs/1409.4842). (Trained by Sergio Guadarrama @sguada)
 
 User-provided models are posted to a public-editable [wiki page](https://github.com/BVLC/caffe/wiki/Model-Zoo).
 

models/bvlc_alexnet/readme.md

@@ -18,6 +18,8 @@ The best validation performance during training was iteration 358,000 with valid
 This model obtains a top-1 accuracy 57.1% and a top-5 accuracy 80.2% on the validation set, using just the center crop.
 (Using the average of 10 crops, (4 + 1 center) * 2 mirror, should obtain a bit higher accuracy.)
 
+This model was trained by Evan Shelhamer @shelhamer
+
 ## License
 
 The data used to train this model comes from the ImageNet project, which distributes its database to researchers who agree to a following term of access:

models/bvlc_googlenet/readme.md

@@ -5,6 +5,7 @@ caffemodel_url: http://dl.caffe.berkeleyvision.org/bvlc_googlenet.caffemodel
 license: non-commercial
 sha1: 405fc5acd08a3bb12de8ee5e23a96bec22f08204
 caffe_commit: bc614d1bd91896e3faceaf40b23b72dab47d44f5
+gist_id: 866e2aa1fd707b89b913
 ---
 
 This model is a replication of the model described in the [GoogleNet](http://arxiv.org/abs/1409.4842) publication. We would like to thank Christian Szegedy for all his help in the replication of GoogleNet model.
@@ -25,6 +26,7 @@ Timings for bvlc_googlenet with cuDNN using batch_size:128 on a K40c:
  - Average Backward pass: 1123.84 ms.
  - Average Forward-Backward: 1688.8 ms.
 
+This model was trained by Sergio Guadarrama @sguada
 
 ## License
 

models/bvlc_reference_caffenet/readme.md

@@ -18,6 +18,8 @@ The best validation performance during training was iteration 313,000 with valid
 This model obtains a top-1 accuracy 57.4% and a top-5 accuracy 80.4% on the validation set, using just the center crop.
 (Using the average of 10 crops, (4 + 1 center) * 2 mirror, should obtain a bit higher accuracy still.)
 
+This model was trained by Jeff Donahue @jeffdonahue
+
 ## License
 
 The data used to train this model comes from the ImageNet project, which distributes its database to researchers who agree to a following term of access:

models/bvlc_reference_rcnn_ilsvrc13/readme.md

@@ -13,6 +13,8 @@ Try the [detection example](http://nbviewer.ipython.org/github/BVLC/caffe/blob/m
 
 *N.B. For research purposes, make use of the official R-CNN package and not this example.*
 
+This model was trained by Ross Girshick @rbgirshick
+
 ## License
 
 The data used to train this model comes from the ImageNet project, which distributes its database to researchers who agree to a following term of access:

models/finetune_flickr_style/readme.md

@@ -15,6 +15,8 @@ The final performance:
     I1017 07:36:17.370730 31333 solver.cpp:247] Iteration 100000, Testing net (#0)
     I1017 07:36:34.248730 31333 solver.cpp:298]     Test net output #0: accuracy = 0.3916
 
+This model was trained by Sergey Karayev @sergeyk
+
 ## License
 
 The Flickr Style dataset contains only URLs to images.