From ee3d0d98e19f1d8177d85af1866fd0ee431fe9ea Mon Sep 17 00:00:00 2001 From: Jules Laplace Date: Sun, 25 Nov 2018 22:19:15 +0100 Subject: moving stuff --- .../entries/Fine-grained Evaluation on Face Detection in the Wild..csv | 1 - 1 file changed, 1 deletion(-) delete mode 100644 datasets/scholar/entries/Fine-grained Evaluation on Face Detection in the Wild..csv (limited to 'datasets/scholar/entries/Fine-grained Evaluation on Face Detection in the Wild..csv') diff --git a/datasets/scholar/entries/Fine-grained Evaluation on Face Detection in the Wild..csv b/datasets/scholar/entries/Fine-grained Evaluation on Face Detection in the Wild..csv deleted file mode 100644 index 249cea3a..00000000 --- a/datasets/scholar/entries/Fine-grained Evaluation on Face Detection in the Wild..csv +++ /dev/null @@ -1 +0,0 @@ -Fine-grained evaluation on face detection in the wild|http://scholar.google.com/https://ieeexplore.ieee.org/abstract/document/7163158/|2015|24|7|6318135921321197431|None|http://scholar.google.com/scholar?cites=6318135921321197431&as_sdt=2005&sciodt=0,5&hl=en|http://scholar.google.com/scholar?cluster=6318135921321197431&hl=en&as_sdt=0,5|None|Current evaluation datasets for face detection, which is of great value in real-world applications, are still somewhat out-of-date. We propose a new face detection dataset MALF (short for Multi-Attribute Labelled Faces), which contains 5,250 images collected from the Internet and~ 12,000 labelled faces. The MALF dataset highlights in two main features: 1) It is the largest dataset for evaluation of face detection in the wild, and the annotation of multiple facial attributes makes it possible for fine-grained performance analysis. 2) To … -- cgit v1.2.3-70-g09d2