Search Results for author: Honglu Zhou

Found 7 papers, 5 papers with code

Laying the Foundations of Deep Long-Term Crowd Flow Prediction

1 code implementation ECCV 2020 Samuel S. Sohn, Honglu Zhou, Seonghyeon Moon, Sejong Yoon, Vladimir Pavlovic, Mubbasir Kapadia

Predicting the crowd behavior in complex environments is a key requirement for crowd and disaster management, architectural design, and urban planning.

Hopper: Multi-hop Transformer for Spatiotemporal Reasoning

1 code implementation ICLR 2021 Honglu Zhou, Asim Kadav, Farley Lai, Alexandru Niculescu-Mizil, Martin Renqiang Min, Mubbasir Kapadia, Hans Peter Graf

We evaluate over CATER dataset and find that Hopper achieves 73. 2% Top-1 accuracy using just 1 FPS by hopping through just a few critical frames.

Graph-Based Generative Representation Learning of Semantically and Behaviorally Augmented Floorplans

no code implementations8 Dec 2020 Vahid Azizi, Muhammad Usman, Honglu Zhou, Petros Faloutsos, Mubbasir Kapadia

We present a floorplan embedding technique that uses an attributed graph to represent the geometric information as well as design semantics and behavioral features of the inhabitants as node and edge attributes.

Representation Learning

GitEvolve: Predicting the Evolution of GitHub Repositories

1 code implementation9 Oct 2020 Honglu Zhou, Hareesh Ravi, Carlos M. Muniz, Vahid Azizi, Linda Ness, Gerard de Melo, Mubbasir Kapadia

Given its crucial role, there is a need to better understand and model the dynamics of GitHub as a social platform.

Representation Learning

Understanding Echo Chambers in E-commerce Recommender Systems

1 code implementation6 Jul 2020 Yingqiang Ge, Shuya Zhao, Honglu Zhou, Changhua Pei, Fei Sun, Wenwu Ou, Yongfeng Zhang

Current research on recommender systems mostly focuses on matching users with proper items based on user interests.

Recommendation Systems

HID: Hierarchical Multiscale Representation Learning for Information Diffusion

2 code implementations19 Apr 2020 Honglu Zhou, Shuyuan Xu, Zuohui Fu, Gerard de Melo, Yongfeng Zhang, Mubbasir Kapadia

In this paper, we present a Hierarchical Information Diffusion (HID) framework by integrating user representation learning and multiscale modeling.

Representation Learning

Deep Crowd-Flow Prediction in Built Environments

no code implementations13 Oct 2019 Samuel S. Sohn, Seonghyeon Moon, Honglu Zhou, Sejong Yoon, Vladimir Pavlovic, Mubbasir Kapadia

In this paper, we propose an approach to instantly predict the long-term flow of crowds in arbitrarily large, realistic environments.

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