Learning Gender with Support Faces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning Object Categories from Google"s Image Search
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
FaceTracer: A Search Engine for Large Collections of Images with Faces
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part IV
Web image mining towards universal age estimator
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Get your jokes right: ask the crowd
MEDI'11 Proceedings of the First international conference on Model and data engineering
People search and activity mining in large-scale community-contributed photos
Proceedings of the 20th ACM international conference on Multimedia
Do you need experts in the crowd?: a case study in image annotation for marine biology
Proceedings of the 10th Conference on Open Research Areas in Information Retrieval
Fish4label: accomplishing an expert task without expert knowledge
Proceedings of the 10th Conference on Open Research Areas in Information Retrieval
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Facial attributes such as gender, race, age, hair style, etc., carry rich information for locating designated persons and profiling the communities from image/video collections (e.g., surveillance videos or photo albums). For plentiful facial attributes in photos and videos, collecting costly manual annotations for training detectors is time-consuming. We propose an automatic facial attribute detection method by exploiting the great amount of weakly labelled photos in social media. Our work can (1) automatically extract training images from the semantic-consistent user groups and (2) filter out noisy training photos by multiple mid-level features (by voting). Moreover, we introduce a method to harvest less-biased negative data for preventing uneven distribution of certain attributes. The experiments show that our approach can automatically acquire training photos for facial attributes and is on par with that by manual annotations.