most citedDilateFormer: Multi-Scale Dilated Transformer for Visual Recognition

12 citations · 18 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV20241 cited

Towards Completeness: A Generalizable Action Proposal Generator for Zero-Shot Temporal Action Localization

Jia-Run Du, Kun-Yu Lin, Jingke Meng +1

To address the zero-shot temporal action localization (ZSTAL) task, existing works develop models that are generalizable to detect and classify actions from unseen categories. They…

cs.CV2024

Human-Centric Transformer for Domain Adaptive Action Recognition

Kun-Yu Lin, Jiaming Zhou, Wei-Shi Zheng

We study the domain adaptation task for action recognition, namely domain adaptive action recognition, which aims to effectively transfer action recognition power from a label-suff…

cs.CV20241 cited

ActionHub: A Large-scale Action Video Description Dataset for Zero-shot Action Recognition

Jiaming Zhou, Junwei Liang, Kun-Yu Lin +2

Zero-shot action recognition (ZSAR) aims to learn an alignment model between videos and class descriptions of seen actions that is transferable to unseen actions. The text queries…

cs.CV20234 cited

Diversifying Spatial-Temporal Perception for Video Domain Generalization

Kun-Yu Lin, Jia-Run Du, Yipeng Gao +2

Video domain generalization aims to learn generalizable video classification models for unseen target domains by training in a source domain. A critical challenge of video domain g…

cs.CV2023

Event-Guided Procedure Planning from Instructional Videos with Text Supervision

An-Lan Wang, Kun-Yu Lin, Jia-Run Du +2

In this work, we focus on the task of procedure planning from instructional videos with text supervision, where a model aims to predict an action sequence to transform the initial…

cs.CV202312 cited

DilateFormer: Multi-Scale Dilated Transformer for Visual Recognition

Jiayu Jiao, Yu-Ming Tang, Kun-Yu Lin +4

As a de facto solution, the vanilla Vision Transformers (ViTs) are encouraged to model long-range dependencies between arbitrary image patches while the global attended receptive f…