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(2.2 MB). 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). Computer Vision beyond the visible: Image understanding through language. . Signal Theory and Communications. [Barcelona]: Universitat Politecnica de Catalunya; 2019.
. Inverse Cooking: Recipe Generation from Food Images. In CVPR. Long Beach, CA, USA: OpenCVF / IEEE; 2019.
. RVOS: End-to-End Recurrent Network for Video Object Segmentation. In CVPR. Long Beach, CA, USA: OpenCVF / IEEE; 2019. (5.76 MB)
(5.76 MB). Wav2Pix: Speech-conditioned Face Generation using Generative Adversarial Networks. In ICASSP. Brighton, UK: IEEE; 2019. (4.42 MB)
(4.42 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). Recurrent Neural Networks for Semantic Instance Segmentation. In CVPR 2018 DeepVision Workshop. 2018. (199.14 KB)
(199.14 KB). Recurrent Neural Networks for Semantic Instance Segmentation. In ECCV 2018 Women in Computer Vision (WiCV) Workshop. 2018. (2.55 MB)
(2.55 MB). Speech-conditioned Face Generation with Deep Adversarial Networks. . 2018. (1.79 MB)
(1.79 MB). Artificial intelligence suggests recipes based on food photos. Boston: MIT News; 2017.
. Learning Cross-modal Embeddings for Cooking Recipes and Food Images. In CVPR. Honolulu, Hawaii, USA: CVF / IEEE; 2017. (3.37 MB)
(3.37 MB). MIT is building a system that can identify a recipe using pictures of food. Techcrunch; 2017.
. Object Retrieval with Deep Convolutional Features. In Deep Learning for Image Processing Applications. Amsterdam, The Netherlands: IOS Press; 2017.
. Recurrent Semantic Instance Segmentation. In NIPS 2017 Women in Machine Learning Workshop (WiML). Long Beach, CA, USA: NIPS 2017 Women in Machine Learning Workshop; 2017. (1.15 MB)
(1.15 MB). Snap a photo, get a recipe: pic2recipe uses AI to predict food ingredients. Digital Trends; 2017.
. Temporal-aware Cross-modal Embeddings for Video and Audio Retrieval. In NIPS 2017 Women in Machine Learning Workshop (WiML). Long Beach, CA, USA: NIPS 2017 Women in Machine Learning Workshop; 2017. (155.1 KB)
(155.1 KB). Assessment of Crowdsourcing and Gamification Loss in User-Assisted Object Segmentation. Multimedia Tools and Applications. 2016;23(75). (5.05 MB)
(5.05 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)
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(22.63 MB). Temporal Activity Detection in Untrimmed Videos with Recurrent Neural Networks. In 1st NIPS Workshop on Large Scale Computer Vision Systems 2016. 2016. (5.66 MB)
(5.66 MB). Temporal Activity Detection in Untrimmed Videos with Recurrent Neural Networks. . 2016. (27.84 MB)
(27.84 MB). Co-filtering human interaction and object segmentation. . 2015. (1.82 MB)
(1.82 MB). Cultural Event Recognition with Visual ConvNets and Temporal Models. In CVPR ChaLearn Looking at People Workshop 2015. 2015. (1.09 MB)
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