activity
20162024
most citedDesign of Efficient Convolutional Layers using Single Intra-channel Convolution, Topological Subdivisioning and Spatial "Bottleneck" Structure

31 citations · 194 across the 38 of their papers we have counts for

collaborators
Showing 2019Show all

8 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.LG2019

Maximum Probability Theorem: A Framework for Probabilistic Learning

Amir Emad Marvasti, Ehsan Emad Marvasti, Ulas Bagci +1

We present a theoretical framework of probabilistic learning derived by Maximum Probability (MP) Theorem shown in the current paper. In this probabilistic framework, a model is def…

cs.CV2019

Slim-CNN: A Light-Weight CNN for Face Attribute Prediction

Ankit Sharma, Hassan Foroosh

We introduce a computationally-efficient CNN micro-architecture Slim Module to design a lightweight deep neural network Slim-Net for face attribute prediction. Slim Modules are con…

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…