118
Voted
MM
2015
ACM
9 years 11 months ago
2015
ACM
With the rapid expansion of online shopping for fashion products, effective fashion recommendation has become an increasingly important problem. In this work, we study the proble...
104
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MM
2015
ACM
9 years 11 months ago
2015
ACM
Crowdsourcing gives researchers the opportunity to collect subjective data quickly, in the real-world, and from a very diverse pool of users. In a long-term study on image aesthet...
116
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MM
2015
ACM
9 years 11 months ago
2015
ACM
The images we encounter throughout our lives make different impressions on us: Some are remembered at first glance, while others are forgotten. This phenomenon is caused by the ...
123
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MM
2015
ACM
9 years 11 months ago
2015
ACM
Large-scale content-based semantic search in video is an interesting and fundamental problem in multimedia analysis and retrieval. Existing methods index a video by the raw concep...
MM
2015
ACM
9 years 11 months ago
2015
ACM
Images without annotations are ubiquitous on the Internet, and recommending tags for them has become a challenging open task in image understanding. A common bottleneck of related...
MM
2015
ACM
9 years 11 months ago
2015
ACM
This paper describes a method to temporally align photo collections that have been created during the same event by different users using their own unsynchronized digital photo c...
MM
2015
ACM
9 years 11 months ago
2015
ACM
Apache Spark is a general-purpose cluster computing system for big data processing and has drawn much attention recently from several fields, such as pattern recognition, machine...
MM
2015
ACM
9 years 11 months ago
2015
ACM
Automatic understanding of photo composition is a valuable technology in multiple areas including digital photography, multimedia advertising, entertainment, and image retrieval. ...
100
click to vote
MM
2015
ACM
9 years 11 months ago
2015
ACM
We present a supervised binary encoding scheme for image retrieval that learns projections by taking into account similarity between classes obtained from output embeddings. Our m...