IIIT-CFW: A Benchmark Database of Cartoon Faces in the Wild
Citations
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Cites background from "IIIT-CFW: A Benchmark Database of C..."
...[23] has more images, but only from 100 subjects....
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...Mishra [23] 100 subjects Caricature: 8,928 images Face: 1,000 images Cartoon recognition...
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...In fact, there are only four publicly available datasets [1, 6, 16, 23] that are related to caricature recognition, shown in Table 1....
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28 citations
Cites background from "IIIT-CFW: A Benchmark Database of C..."
...sketches from three caricature datasets [58]–[60], and group them into three collections of sketch styles based on the...
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25 citations
Cites background from "IIIT-CFW: A Benchmark Database of C..."
...To answer the aforementioned question, two natural problems raise our concerns: 1) what is the desirable need in cartoon dataset? 2) what is the relationship between human faces and cartoon ones? In this less-explored recognition of virtual media, few datasets [2, 7, 14, 21] have been proposed for specific purposes, which can be roughly grouped into two categories....
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...WebCaricature [14] Caricature recognition 12,016 252 ✗ ✓ Facial Landmark IIIT-CFW [21] Caricature recognition 8,928 100 ✗ ✗ Pose (1D), Age Manga109 [7] Cartoon detection&retrival 21,142 Unified ✓ ✗...
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...IIIT-CFW can be used for a wide spectrum of problems due to the fact that it contains detailed annotations such as type of cartoon, pose, expression, age group, and etc.WebCaricature [14] is a large photograph-caricature dataset consisting of 6,042 caricatures and 5,974 photographs from 252 persons collected from the web....
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...IIIT-CFW [21] established a challenging dataset of 8,928 annotated unconstrained cartoon faces of 100 international celebrities....
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...For example, IIIT-CFW [21] contains 8,928 annotated cartoon faces of 100 international celebrities....
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24 citations
References
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Additional excerpts
...The Google and Facebook database contains 200Million and 4.4 Million faces of 4030 and 8 Million characters respectively....
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...Since cartoon 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 Databases Variation Size Target applications R G P E A (# people, # images) ORL [11] X X X X X (40, 400) P1 Yale [12] X X × X X (15, 165) P1 Indian Face [13] × X X X X (40, 440) P1 LFW [14] X X X × X (5749, 13233) P1, P2 Texas 3D [15][16] X X × X X (105, 1149) P1 FEI [17] × X X X X (200, 2800) P1 PubFig83 [18] X X X X X (100, 8300) P2 Celeb Faces [19] X X X X X (5346, 87628) P1,P2 IMFDB [20] × X X X X (100, 34512) P1, P2 LWF [22] X X X X X (1500, 8500) P1, P2 FaceScrub [21] X X X X X (530, 106863) P1,P3 Facebook [5] - - - - - (200M, 8M) * Google [4] - - - - - (4.4M, 4030M) * VGG [6] X X X X X (2363, 2.6M) P1,P2 The IIIT-CFW X X X X X (100, 8927) P1,P2,P3,P4,P5,P6,P7 Table 1....
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...These face databases introduced by Google and Facebook are the largest in size....
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...These real faces are harvested from Google image search and can be used as query for photo2cartoon retrieval and database for cartoon2photo retrieval....
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...The CFW is harvested from Google image search....
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6,384 citations
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Additional excerpts
...Databases Variation Size Target applications R G P E A (# people, # images) ORL [11] X X X X X (40, 400) P1 Yale [12] X X × X X (15, 165) P1 Indian Face [13] × X X X X (40, 440) P1 LFW [14] X X X × X (5749, 13233) P1, P2 Texas 3D [15][16] X X × X X (105, 1149) P1 FEI [17] × X X X X (200, 2800) P1 PubFig83 [18] X X X X X (100, 8300) P2 Celeb Faces [19] X X X X X (5346, 87628) P1,P2 IMFDB [20] × X X X X (100, 34512) P1, P2 LWF [22] X X X X X (1500, 8500) P1, P2 FaceScrub [21] X X X X X (530, 106863) P1,P3 Facebook [5] - - - - - (200M, 8M) * Google [4] - - - - - (4....
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...Since cartoon 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 Databases Variation Size Target applications R G P E A (# people, # images) ORL [11] X X X X X (40, 400) P1 Yale [12] X X × X X (15, 165) P1 Indian Face [13] × X X X X (40, 440) P1 LFW [14] X X X × X (5749, 13233) P1, P2 Texas 3D [15][16] X X × X X (105, 1149) P1 FEI [17] × X X X X (200, 2800) P1 PubFig83 [18] X X X X X (100, 8300) P2 Celeb Faces [19] X X X X X (5346, 87628) P1,P2 IMFDB [20] × X X X X (100, 34512) P1, P2 LWF [22] X X X X X (1500, 8500) P1, P2 FaceScrub [21] X X X X X (530, 106863) P1,P3 Facebook [5] - - - - - (200M, 8M) * Google [4] - - - - - (4.4M, 4030M) * VGG [6] X X X X X (2363, 2.6M) P1,P2 The IIIT-CFW X X X X X (100, 8927) P1,P2,P3,P4,P5,P6,P7 Table 1....
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