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Diffstat (limited to 'site/content/pages/datasets')
| -rw-r--r-- | site/content/pages/datasets/brainwash/index.md | 37 | ||||
| -rw-r--r-- | site/content/pages/datasets/cofw/index.md | 2 | ||||
| -rw-r--r-- | site/content/pages/datasets/lfw/index.md | 2 |
3 files changed, 38 insertions, 3 deletions
diff --git a/site/content/pages/datasets/brainwash/index.md b/site/content/pages/datasets/brainwash/index.md new file mode 100644 index 00000000..d1dbd581 --- /dev/null +++ b/site/content/pages/datasets/brainwash/index.md @@ -0,0 +1,37 @@ +------------ + +status: published +title: Brainwash +desc: Brainwash +slug: Brainwash +color: #ff0000 +image: assets/background.jpg +published: 2019-2-23 +updated: 2019-2-23 +authors: Adam Harvey + +------------ + +# Brainwash + ++ Year: 2015 ++ Images: 11,917 ++ Faces: 91,146 ++ Origin: Dropcam footage ++ Created by: Stanford + + +<!--header--> + + + +COFW is "is designed to benchmark face landmark algorithms in realistic conditions, which include heavy occlusions and large shape variations" [Robust face landmark estimation under occlusion]. + + +-------- + +RESEARCH below this line + +--- + +add research about Brainwash here
\ No newline at end of file diff --git a/site/content/pages/datasets/cofw/index.md b/site/content/pages/datasets/cofw/index.md index 1d2a879c..7a668cec 100644 --- a/site/content/pages/datasets/cofw/index.md +++ b/site/content/pages/datasets/cofw/index.md @@ -1,6 +1,6 @@ ------------ -status: draft +status: published title: Caltech Occluded Faces in The Wild desc: COFW: Caltech Occluded Faces in The Wild slug: cofw diff --git a/site/content/pages/datasets/lfw/index.md b/site/content/pages/datasets/lfw/index.md index f92cd25f..83245470 100644 --- a/site/content/pages/datasets/lfw/index.md +++ b/site/content/pages/datasets/lfw/index.md @@ -52,9 +52,7 @@ map To visualize the types of photos in the dataset without explicitly publishing individual's identities a generative adversarial network (GAN) was trained on the entire dataset. The images in this video show a neural network learning the visual latent space and then interpolating between archetypical identities within the LFW dataset.  -  -  ### Citations |