activity
20192022
most citedRSPNet: Relative Speed Perception for Unsupervised Video Representation Learning

16 citations · 53 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CV202216 cited

Weakly-Supervised Multi-Granularity Map Learning for Vision-and-Language Navigation

Peihao Chen, Dongyu Ji, Kunyang Lin +4

We address a practical yet challenging problem of training robot agents to navigate in an environment following a path described by some language instructions. The instructions oft…

cs.CV202016 cited

RSPNet: Relative Speed Perception for Unsupervised Video Representation Learning

Peihao Chen, Deng Huang, Dongliang He +5

We study unsupervised video representation learning that seeks to learn both motion and appearance features from unlabeled video only, which can be reused for downstream tasks such…

cs.CV20204 cited

Location-aware Graph Convolutional Networks for Video Question Answering

Deng Huang, Peihao Chen, Runhao Zeng +3

We addressed the challenging task of video question answering, which requires machines to answer questions about videos in a natural language form. Previous state-of-the-art method…

cs.CV202015 cited

Dense Regression Network for Video Grounding

Runhao Zeng, Haoming Xu, Wenbing Huang +3

We address the problem of video grounding from natural language queries. The key challenge in this task is that one training video might only contain a few annotated starting/endin…

eess.IV2020

A Thorough Comparison Study on Adversarial Attacks and Defenses for Common Thorax Disease Classification in Chest X-rays

Chendi Rao, Jiezhang Cao, Runhao Zeng +4

Recently, deep neural networks (DNNs) have made great progress on automated diagnosis with chest X-rays images. However, DNNs are vulnerable to adversarial examples, which may caus…

cs.CV2019

Graph Convolutional Networks for Temporal Action Localization

Runhao Zeng, Wenbing Huang, Mingkui Tan +4

Most state-of-the-art action localization systems process each action proposal individually, without explicitly exploiting their relations during learning. However, the relations b…