activity
20192026
most citedSpatio-Temporal Fusion Networks for Action Recognition

12 citations · 50 across the 28 of their papers we have counts for

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Showing 2019Show all

5 papers · 1 filter

cs.CV2019★ 8 cited

Self-Attention Network for Skeleton-based Human Action Recognition

Sangwoo Cho, Muhammad Hasan Maqbool, Fei Liu +1

Skeleton-based action recognition has recently attracted a lot of attention. Researchers are coming up with new approaches for extracting spatio-temporal relations and making consi…

cs.CL2019★ 1 cited

Multi-Document Summarization with Determinantal Point Processes and Contextualized Representations

Sangwoo Cho, Chen Li, Dong Yu +2

Emerged as one of the best performing techniques for extractive summarization, determinantal point processes select the most probable set of sentences to form a summary according t…

cs.CV2019★ 12 cited

Spatio-Temporal Fusion Networks for Action Recognition

Sangwoo Cho, Hassan Foroosh

The video based CNN works have focused on effective ways to fuse appearance and motion networks, but they typically lack utilizing temporal information over video frames. In this w…

cs.CV2019★ 9 cited

A Temporal Sequence Learning for Action Recognition and Prediction

Sangwoo Cho, Hassan Foroosh

In this work\footnote {This work was supported in part by the National Science Foundation under grant IIS-1212948.}, we present a method to represent a video with a sequence of wor…

cs.CL2019★ 4 cited

Improving the Similarity Measure of Determinantal Point Processes for Extractive Multi-Document Summarization

Sangwoo Cho, Logan Lebanoff, Hassan Foroosh +1

The most important obstacles facing multi-document summarization include excessive redundancy in source descriptions and the looming shortage of training data. These obstacles prev…