activity
20162023
most citedFocal Visual-Text Attention for Visual Question Answering

76 citations · 204 across the 13 of their papers we have counts for

collaborators

13 papers

cs.CV2023

Spatial-Temporal Alignment Network for Action Recognition

Jinhui Ye, Junwei Liang

This paper studies introducing viewpoint invariant feature representations in existing action recognition architecture. Despite significant progress in action recognition, efficien…

cs.CV2022★ 17 cited

Text-Adaptive Multiple Visual Prototype Matching for Video-Text Retrieval

Chengzhi Lin, Ancong Wu, Junwei Liang +4

Cross-modal retrieval between videos and texts has gained increasing research interest due to the rapid emergence of videos on the web. Generally, a video contains rich instance an…

cs.CV2022★ 2 cited

Multi-dataset Training of Transformers for Robust Action Recognition

Junwei Liang, Enwei Zhang, Jun Zhang +1

We study the task of robust feature representations, aiming to generalize well on multiple datasets for action recognition. We build our method on Transformers for its efficacy. Al…

cs.CV2020★ 3 cited

Spatial-Temporal Alignment Network for Action Recognition and Detection

Junwei Liang, Liangliang Cao, Xuehan Xiong +2

This paper studies how to introduce viewpoint-invariant feature representations that can help action recognition and detection. Although we have witnessed great progress of action…

cs.CV2020★ 9 cited

MSNet: A Multilevel Instance Segmentation Network for Natural Disaster Damage Assessment in Aerial Videos

Xiaoyu Zhu, Junwei Liang, Alexander Hauptmann

In this paper, we study the problem of efficiently assessing building damage after natural disasters like hurricanes, floods or fires, through aerial video analysis. We make two ma…

cs.CV2020★ 15 cited

SimAug: Learning Robust Representations from Simulation for Trajectory Prediction

Junwei Liang, Lu Jiang, Alexander Hauptmann

This paper studies the problem of predicting future trajectories of people in unseen cameras of novel scenarios and views. We approach this problem through the real-data-free setti…