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] . Learning Cross-modal Embeddings for Cooking Recipes and Food Images. In CVPR. Honolulu, Hawaii, USA: CVF / IEEE; 2017. 
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(3.37 MB). Inverse Cooking: Recipe Generation from Food Images. In CVPR. Long Beach, CA, USA: OpenCVF / IEEE; 2019.
. Insight DCU at TRECVID 2015. In TRECVID 2015 Workshop. Gaithersburg, MD, USA: NIST; 2015. (2.13 MB)
(2.13 MB). Insight Centre for Data Analytics (DCU) at TRECVid 2014: Instance Search and Semantic Indexing Tasks. In 2014 TRECVID Workshop. Orlando, Florida (USA): National Institute of Standards and Technology (NIST); 2014. (2.45 MB)
(2.45 MB). Faster R-CNN Features for Instance Search. In CVPR Workshop Deep Vision. 2016. (2.77 MB)
(2.77 MB). Exploring EEG for Object Detection and Retrieval. In ACM International Conference on Multimedia Retrieval (ICMR) . Shanghai, China; 2015. (5.37 MB)
(5.37 MB). Diving Deep into Sentiment: Understanding Fine-tuned CNNs for Visual Sentiment Prediction. In 1st International Workshop on Affect and Sentiment in Multimedia. Brisbane, Australia: ACM; 2015. (506.22 KB)
(506.22 KB). Cultural Event Recognition with Visual ConvNets and Temporal Models. In CVPR ChaLearn Looking at People Workshop 2015. 2015. (1.09 MB)
(1.09 MB). Crowdsourced Object Segmentation with a Game. In ACM Workshop on Crowdsourcing for Multimedia (CrowdMM). Barcelona; 2013. (1.22 MB)
(1.22 MB). Cross-modal Embeddings for Video and Audio Retrieval. In ECCV 2018 Women in Computer Vision Workshop. Munich, Germany: Springer; 2018. (1.07 MB)
(1.07 MB). Click’n’Cut: Crowdsourced Interactive Segmentation with Object Candidates. In 3rd International ACM Workshop on Crowdsourcing for Multimedia (CrowdMM). Orlando, Florida (USA); 2014. (1017.73 KB)
(1017.73 KB). Budget-aware Semi-Supervised Semantic and Instance Segmentation. In CVPR 2019 DeepVision Workshop. Long Beach, CA, USA: OpenCVF; 2019. (6.59 MB)
(6.59 MB). Bags of Local Convolutional Features for Scalable Instance Search. In ACM International Conference on Multimedia Retrieval (ICMR). New York City, NY; USA: ACM; 2016. (3.73 MB)
(3.73 MB). Object Retrieval with Deep Convolutional Features. In Deep Learning for Image Processing Applications. Amsterdam, The Netherlands: IOS Press; 2017.