activity
20182024
most citedAdaAttN: Revisit Attention Mechanism in Arbitrary Neural Style Transfer

26 citations · 226 across the 38 of their papers we have counts for

collaborators
Showing 2019Show all

6 papers · 1 filter

cs.CV2019★ 14 cited

Multi-Label Classification with Label Graph Superimposing

Ya Wang, Dongliang He, Fu Li +4

Images or videos always contain multiple objects or actions. Multi-label recognition has been witnessed to achieve pretty performance attribute to the rapid development of deep lea…

cs.CV2019

TruNet: Short Videos Generation from Long Videos via Story-Preserving Truncation

Fan Yang, Xiao Liu, Dongliang He +5

In this work, we introduce a new problem, named as {\em story-preserving long video truncation}, that requires an algorithm to automatically truncate a long-duration video into mul…

cs.CV2019

Deep Concept-wise Temporal Convolutional Networks for Action Localization

Xin Li, Tianwei Lin, Xiao Liu +7

Existing action localization approaches adopt shallow temporal convolutional networks (\ie, TCN) on 1D feature map extracted from video frames. In this paper, we empirically find t…

cs.CV2019

Multi-Agent Reinforcement Learning Based Frame Sampling for Effective Untrimmed Video Recognition

Wenhao Wu, Dongliang He, Xiao Tan +2

Video Recognition has drawn great research interest and great progress has been made. A suitable frame sampling strategy can improve the accuracy and efficiency of recognition. How…

cs.CV2019★ 1 cited

Adapting Image Super-Resolution State-of-the-arts and Learning Multi-model Ensemble for Video Super-Resolution

Chao Li, Dongliang He, Xiao Liu +2

Recently, image super-resolution has been widely studied and achieved significant progress by leveraging the power of deep convolutional neural networks. However, there has been li…

cs.CV2019★ 19 cited

Read, Watch, and Move: Reinforcement Learning for Temporally Grounding Natural Language Descriptions in Videos

Dongliang He, Xiang Zhao, Jizhou Huang +3

The task of video grounding, which temporally localizes a natural language description in a video, plays an important role in understanding videos. Existing studies have adopted st…