activity
20182022
most citedRevisiting Heterophily For Graph Neural Networks

70 citations · 109 across the 10 of their papers we have counts for

collaborators

15 papers

cs.LG202270 cited

Revisiting Heterophily For Graph Neural Networks

Sitao Luan, Chenqing Hua, Qincheng Lu +5

Graph Neural Networks (GNNs) extend basic Neural Networks (NNs) by using graph structures based on the relational inductive bias (homophily assumption). While GNNs have been common…

cs.CV2022

Human Instance Segmentation and Tracking via Data Association and Single-stage Detector

Lu Cheng, Mingbo Zhao

Human video instance segmentation plays an important role in computer understanding of human activities and is widely used in video processing, video surveillance, and human modeli…

cs.LG2022

Temporal Abstractions-Augmented Temporally Contrastive Learning: An Alternative to the Laplacian in RL

Akram Erraqabi, Marlos C. Machado, Mingde Zhao +4

In reinforcement learning, the graph Laplacian has proved to be a valuable tool in the task-agnostic setting, with applications ranging from skill discovery to reward shaping. Rece…

cs.HC2021

Classifying In-Place Gestures with End-to-End Point Cloud Learning

Lizhi Zhao, Xuequan Lu, Min Zhao +1

Walking in place for moving through virtual environments has attracted noticeable attention recently. Recent attempts focused on training a classifier to recognize certain patterns…

cs.AI202111 cited

On the Evaluation of Vision-and-Language Navigation Instructions

Ming Zhao, Peter Anderson, Vihan Jain +4

Vision-and-Language Navigation wayfinding agents can be enhanced by exploiting automatically generated navigation instructions. However, existing instruction generators have not be…

cs.CV202020 cited

A Hierarchical Multi-Modal Encoder for Moment Localization in Video Corpus

Bowen Zhang, Hexiang Hu, Joonseok Lee +5

Identifying a short segment in a long video that semantically matches a text query is a challenging task that has important application potentials in language-based video search, b…