4 citations · 6 across the 2 of their papers we have counts for
7 papers · 1 filter
Efficient Training of Large Vision Models via Advanced Automated Progressive Learning
Changlin Li, Jiawei Zhang, Sihao Lin +4
The rapid advancements in Large Vision Models (LVMs), such as Vision Transformers (ViTs) and diffusion models, have led to an increasing demand for computational resources, resulti…
Open-Vocabulary 3D Semantic Segmentation with Text-to-Image Diffusion Models
Xiaoyu Zhu, Hao Zhou, Pengfei Xing +6
In this paper, we investigate the use of diffusion models which are pre-trained on large-scale image-caption pairs for open-vocabulary 3D semantic understanding. We propose a novel…
Adversarially Masked Video Consistency for Unsupervised Domain Adaptation
Xiaoyu Zhu, Junwei Liang, Po-Yao Huang +1
We study the problem of unsupervised domain adaptation for egocentric videos. We propose a transformer-based model to learn class-discriminative and domain-invariant feature repres…
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…
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…
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…