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Social event detection with robust high-order co-clustering
TLDR
Social Event Detection with Robust High-Order Co-Clustering (SED-RHOCC) algorithm is proposed and it includes two steps: 1) coarse event detection, 2) clusters and samples refinement. Expand
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Being a Supercook: Joint Food Attributes and Multimodal Content Modeling for Recipe Retrieval and Exploration
TLDR
This paper considers the problem of recipe-oriented image-ingredient correlation learning with multi-attributes for recipe retrieval and exploration. Expand
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Cross-Platform Multi-Modal Topic Modeling for Personalized Inter-Platform Recommendation
TLDR
We propose a cross-platform multi-modal topic model, which is capable of differentiating between shared topics and platform-specific topics, and aligning topics on different modalities across different platforms. Expand
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A Survey on Food Computing
TLDR
We present the first comprehensive survey that targets the study of computing technology for the food area and present a comprehensive overview of various emerging concepts, methods, and tasks. Expand
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Cross-Platform Emerging Topic Detection and Elaboration from Multimedia Streams
TLDR
Robust Cross-Platform Multimedia Co-Clustering (RCPMM-CC) is proposed to detect emerging topics using multimedia streams cross different online platforms. Expand
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Multi-Scale Multi-View Deep Feature Aggregation for Food Recognition
TLDR
We propose a multi-scale multi-view feature aggregation (MSMVFA) scheme for food recognition that achieves state-of-the-art performance. Expand
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Few-shot Food Recognition via Multi-view Representation Learning
TLDR
We propose a Multi-View Few-Shot Learning (MVFSL) framework to explore additional ingredient information for few-shot food recognition. Expand
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You Are What You Eat: Exploring Rich Recipe Information for Cross-Region Food Analysis
TLDR
In this paper, we perform the first cross-region recipe analysis by jointly using the recipe ingredients, food images, and attributes such as cuisine and course (e.g., main dish and dessert). Expand
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A Delicious Recipe Analysis Framework for Exploring Multi-Modal Recipes with Various Attributes
TLDR
We propose a delicious recipe analysis framework to incorporate various types of continuous and discrete attribute features and multi-modal information from recipes to benefit various applications like summary and recommendation. Expand
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Multimodal Spatio-Temporal Theme Modeling for Landmark Analysis
TLDR
We propose a probabilistic topic model called Multimodal Spatio-Temporal Theme Modeling (mmSTTM) to learn general, local, and temporal themes, which span a low-dimensional theme space. Expand
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