Semantic Search in Internet Videos?
What's in this web page?This page contains a list of features on two benchmarks MED13 and MED14 used in our paper , as well as the ranked list returned by our system. The shared data are expected to help:
MED16 Train and Test features are avialable. See details here.
1) reproduce our state-of-the-art results;
2) benefit related tasks such as video recommendation, hyperlinking and recounting.
 Junwei Liang, Lu Jiang, Deyu Meng, Alexander Hauptmann. Learning to Detect Concepts from Webly-Labeled Video Data. In IJCAI, 2016.
*Please cite the corresponding papers for using our features (32,000 Internet videos).
 Y. Miao, F. Metze, and S. Rawat. Deep maxout networks for low-resource speech recognition. In ASRU, 2013.
 S.-I. Yu, L. Jiang, Z. Xu, et al. CMU-informedia@TRECVID 2014. In TRECVID, 2014.
 L. Jiang, D. Meng, S.-I. Yu, Z. Lan, S. Shan, and A. G. Hauptmann. Self-paced learning with diversity. In NIPS, 2014.
 B. Thomee, D. A. Shamma, G. Friedland, B. Elizalde, K. Ni, D. Poland, D. Borth, and L.-J. Li. The new data and new challenges in multimedia research. arXiv preprint arXiv:1503.01817, 2015.
 A. Karpathy, G. Toderici, S. Shetty, T. Leung, R. Sukthankar, and L. Fei-Fei. Large-scale video classification with convolutional neural networks. In CVPR, 2014.
 P. Over, G. Awad, M. Michel, J. Fiscus, G. Sanders, W. Kraaij, A. F. Smeaton, and G. QuŽeenot. TRECVID 2014 – an overview of the goals, tasks, data, evaluation mechanisms and metrics. In TRECVID, 2014.
 S.-I. Yu, L. Jiang, and A. Hauptmann. Instructional videos for unsupervised harvesting and learning of action examples. In MM, 2014.
 H. Wang and C. Schmid. Action recognition with improved trajectories. In ICCV, 2013.
Retrieved Ranked List:*The ranked list are specified in NIST's standard csv format (http://www.nist.gov/itl/iad/mig/med14.cfm).
Published Results on the MED13Test dataset:
 A. Habibian, T. Mensink, and C. G. Snoek. Composite concept discovery for zero-shot video event detection. In ICMR, 2014.
 M. Mazloom, X. Li, and C. G. Snoek. Few-example video event retrieval using tag propagation. In ICMR, 2014.
 L. Jiang, T. Mitamura, S.-I. Yu, and A. G. Hauptmann. Zero-example event search using multimodal pseudo relevance feedback. In ICMR, 2014.
 H. Lee. Analyzing complex events and human actions in” in-the-wild” videos. In UMD Ph.D Theses and Dissertations, 2014.
 S. Wu, S. Bondugula, F. Luisier, X. Zhuang, and P. Natarajan. Zero-shot event detection using multi-modal fusion of weakly supervised concepts. In CVPR, 2014.
 L. Jiang, D. Meng, T. Mitamura, and A. G. Hauptmann. Easy samples first: Self-paced reranking for zero-example multimedia search. In MM, 2014.
 L. Jiang, S.-I Yu, D. Meng, T. Mitamura, A. G. Hauptmann. Bridging the Ultimate Semantic Gap: A Semantic Search Engine for Internet Videos. In ICMR 2015.
Recommandations for building a state-of-the-art system:
Screenshot of our Prototype System :
*Please contact us if you would like to access our prototype system.
 S. Xu, H. Li, X. Chang, S.-I. Yu, X. Du, X. Li, L. Jiang, Z. Mao, Z. Lan, S. Burger, and A. Hauptmann. Incremental multimodal query construction for video search. In ICMR, 2015.
Citation:Lu Jiang, Shoou-I Yu, Deyu Meng, Teruko Mitamura, Alexander Hauptmann. Bridging the Ultimate Semantic Gap: A Semantic Search Engine for Internet Videos.
In ACM International Conference on Multimedia Retrieval (ICMR). 2015. [BibTex | supplementary materials]
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