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/The Do's and Don'ts for CNN-based Face Verification.csv | 1 - 1 file changed, 1 deletion(-) delete mode 100644 datasets/scholar/entries/The Do's and Don'ts for CNN-based Face Verification.csv (limited to 'datasets/scholar/entries/The Do's and Don'ts for CNN-based Face Verification.csv') diff --git a/datasets/scholar/entries/The Do's and Don'ts for CNN-based Face Verification.csv b/datasets/scholar/entries/The Do's and Don'ts for CNN-based Face Verification.csv deleted file mode 100644 index d494c943..00000000 --- a/datasets/scholar/entries/The Do's and Don'ts for CNN-based Face Verification.csv +++ /dev/null @@ -1 +0,0 @@ -The Do's and Don'ts for CNN-based Face Verification.|http://openaccess.thecvf.com/content_ICCV_2017_workshops/papers/w37/Bansal_The_Dos_and_ICCV_2017_paper.pdf|2017|21|7|16583671830808674747|http://openaccess.thecvf.com/content_ICCV_2017_workshops/papers/w37/Bansal_The_Dos_and_ICCV_2017_paper.pdf|http://scholar.google.com/scholar?cites=16583671830808674747&as_sdt=2005&sciodt=0,5&hl=en|http://scholar.google.com/scholar?cluster=16583671830808674747&hl=en&as_sdt=0,5|None|While the research community appears to have developed a consensus on the methods of acquiring annotated data, design and training of CNNs, many questions still remain to be answered. In this paper, we explore the following questions that are critical to face recognition research:(i) Can we train on still images and expect the systems to work on videos?(ii) Are deeper datasets better than wider datasets?(iii) Does adding label noise lead to improvement in performance of deep networks?(iv) Is alignment needed for face … -- cgit v1.2.3-70-g09d2