activity
20162026
most citedUnsupervised, Efficient and Semantic Expertise Retrieval

57 citations · 218 across the 37 of their papers we have counts for

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Showing 2023Show all

9 papers · 1 filter

cs.CV2023★ 1 cited

Conditional Modeling Based Automatic Video Summarization

Jia-Hong Huang, Chao-Han Huck Yang, Pin-Yu Chen +2

The aim of video summarization is to shorten videos automatically while retaining the key information necessary to convey the overall story. Video summarization methods mainly rely…

cs.LG2023

Prototype-Enhanced Hypergraph Learning for Heterogeneous Information Networks

Shuai Wang, Jiayi Shen, Athanasios Efthymiou +4

The variety and complexity of relations in multimedia data lead to Heterogeneous Information Networks (HINs). Capturing the semantics from such networks requires approaches capable…

cs.LG2023★ 1 cited

Multimodal Temporal Fusion Transformers Are Good Product Demand Forecasters

Maarten Sukel, Stevan Rudinac, Marcel Worring

Multimodal demand forecasting aims at predicting product demand utilizing visual, textual, and contextual information. This paper proposes a method for multimodal product demand fo…

cs.CV2023

Causal Video Summarizer for Video Exploration

Jia-Hong Huang, Chao-Han Huck Yang, Pin-Yu Chen +2

Recently, video summarization has been proposed as a method to help video exploration. However, traditional video summarization models only generate a fixed video summary which is…

cs.CV2023★ 3 cited

Query-based Video Summarization with Pseudo Label Supervision

Jia-Hong Huang, Luka Murn, Marta Mrak +1

Existing datasets for manually labelled query-based video summarization are costly and thus small, limiting the performance of supervised deep video summarization models. Self-supe…

cs.CV2023

Causalainer: Causal Explainer for Automatic Video Summarization

Jia-Hong Huang, Chao-Han Huck Yang, Pin-Yu Chen +2

The goal of video summarization is to automatically shorten videos such that it conveys the overall story without losing relevant information. In many application scenarios, improp…