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Diffstat (limited to 'site/datasets/verified/uccs.csv')
| -rw-r--r-- | site/datasets/verified/uccs.csv | 12 |
1 files changed, 5 insertions, 7 deletions
diff --git a/site/datasets/verified/uccs.csv b/site/datasets/verified/uccs.csv index d7c84820..1cbefd32 100644 --- a/site/datasets/verified/uccs.csv +++ b/site/datasets/verified/uccs.csv @@ -1,9 +1,7 @@ id,country,dataset_name,key,lat,lng,loc,loc_type,paper_id,paper_type,paper_url,title,year 0,,UCCS,uccs,0.0,0.0,,,,main,,Large scale unconstrained open set face database,2013 -1,United States,UCCS,uccs,41.70456775,-86.23822026,University of Notre Dame,edu,841855205818d3a6d6f85ec17a22515f4f062882,citation,https://arxiv.org/pdf/1805.11529.pdf,Low Resolution Face Recognition in the Wild,2018 -2,United States,UCCS,uccs,40.11571585,-88.22750772,Beckman Institute,edu,288d2704205d9ca68660b9f3a8fda17e18329c13,citation,https://arxiv.org/pdf/1601.04153.pdf,Studying Very Low Resolution Recognition Using Deep Networks,2016 -3,United States,UCCS,uccs,38.8920756,-104.79716389,"University of Colorado, Colorado Springs",edu,d4f1eb008eb80595bcfdac368e23ae9754e1e745,citation,,Unconstrained Face Detection and Open-Set Face Recognition Challenge,2017 -4,United Kingdom,UCCS,uccs,51.5247272,-0.03931035,Queen Mary University of London,edu,2306b2a8fba28539306052764a77a0d0f5d1236a,citation,https://arxiv.org/pdf/1804.09691.pdf,Surveillance Face Recognition Challenge,2018 -5,United Kingdom,UCCS,uccs,55.378051,-3.435973,"Vision Semantics Ltd, UK",edu,2306b2a8fba28539306052764a77a0d0f5d1236a,citation,https://arxiv.org/pdf/1804.09691.pdf,Surveillance Face Recognition Challenge,2018 -6,China,UCCS,uccs,39.9808333,116.34101249,Beihang University,edu,c50e498ede6f5216cffd0645e747ce67fae2096a,citation,https://arxiv.org/pdf/1811.09998.pdf,Low-Resolution Face Recognition in the Wild via Selective Knowledge Distillation,2018 -7,China,UCCS,uccs,39.97426,116.21589,"Institute of Information Engineering, CAS, Beijing, China",edu,c50e498ede6f5216cffd0645e747ce67fae2096a,citation,https://arxiv.org/pdf/1811.09998.pdf,Low-Resolution Face Recognition in the Wild via Selective Knowledge Distillation,2018 +1,United States,UCCS,uccs,40.11571585,-88.22750772,Beckman Institute,edu,288d2704205d9ca68660b9f3a8fda17e18329c13,citation,https://arxiv.org/pdf/1601.04153.pdf,Studying Very Low Resolution Recognition Using Deep Networks,2016 +2,United States,UCCS,uccs,38.8920756,-104.79716389,"University of Colorado, Colorado Springs",edu,d4f1eb008eb80595bcfdac368e23ae9754e1e745,citation,,Unconstrained Face Detection and Open-Set Face Recognition Challenge,2017 +3,United States,UCCS,uccs,41.70456775,-86.23822026,University of Notre Dame,edu,841855205818d3a6d6f85ec17a22515f4f062882,citation,https://arxiv.org/pdf/1805.11529.pdf,Low Resolution Face Recognition in the Wild,2018 +4,China,UCCS,uccs,39.9808333,116.34101249,Beihang University,edu,c50e498ede6f5216cffd0645e747ce67fae2096a,citation,https://arxiv.org/pdf/1811.09998.pdf,Low-Resolution Face Recognition in the Wild via Selective Knowledge Distillation,2018 +5,China,UCCS,uccs,39.97426,116.21589,"Institute of Information Engineering, CAS, Beijing, China",edu,c50e498ede6f5216cffd0645e747ce67fae2096a,citation,https://arxiv.org/pdf/1811.09998.pdf,Low-Resolution Face Recognition in the Wild via Selective Knowledge Distillation,2018 |