no code implementations • ECCV 2020 • Niamul Quader, Juwei Lu, Peng Dai, Wei Li
State-of-the-art approaches to video-based action and gesture recognition often employ two key concepts: First, they employ multistream processing; second, they use an ensemble of convolutional networks.
Ranked #1 on Action Classification on Jester test
1 code implementation • ECCV 2020 • Niamul Quader, Md Mafijul Islam Bhuiyan, Juwei Lu, Peng Dai, Wei Li
We propose novel approaches for simultaneously identifying important weights of a convolutional neural network (ConvNet) and providing more attention to the important weights during training.
no code implementations • 24 Jan 2024 • Chuan Guo, Yuxuan Mu, Xinxin Zuo, Peng Dai, Youliang Yan, Juwei Lu, Li Cheng
Building upon this, we present a novel generative model that produces diverse stylization results of a single motion (latent) code.
no code implementations • CVPR 2023 • Renjing Pei, Jianzhuang Liu, Weimian Li, Bin Shao, Songcen Xu, Peng Dai, Juwei Lu, Youliang Yan
Pre-training a vison-language model and then fine-tuning it on downstream tasks have become a popular paradigm.
no code implementations • ICCV 2023 • Bin Shao, Jianzhuang Liu, Renjing Pei, Songcen Xu, Peng Dai, Juwei Lu, Weimian Li, Youliang Yan
However, compared to image-language pre-training, VLP has lagged far behind due to the lack of large amounts of video-text pairs.
no code implementations • 25 Jul 2022 • Zhixiang Chi, Rasoul Mohammadi Nasiri, Zheng Liu, Yuanhao Yu, Juwei Lu, Jin Tang, Konstantinos N Plataniotis
However, none of the published VFI works considers the spatially non-uniform characteristics of the interpolation error (IE).
no code implementations • 21 Dec 2021 • Varshanth R. Rao, Md Ibrahim Khalil, Haoda Li, Peng Dai, Juwei Lu
In this paper, we propose a framework centering around a novel architecture called the Event Decomposition Recomposition Network (EDRNet) to tackle the Audio-Visual Event (AVE) localization problem in the supervised and weakly supervised settings.
no code implementations • 11 Dec 2021 • Hanwen Liang, Niamul Quader, Zhixiang Chi, Lizhe Chen, Peng Dai, Juwei Lu, Yang Wang
Recent self-supervised video representation learning methods have found significant success by exploring essential properties of videos, e. g. speed, temporal order, etc.
no code implementations • ICCV 2021 • Deepak Sridhar, Niamul Quader, Srikanth Muralidharan, Yaoxin Li, Peng Dai, Juwei Lu
Our attention mechanism outperforms prior self-attention modules such as the squeeze-and-excitation in action detection task.
1 code implementation • ICCV 2021 • Hanwen Liang, Qiong Zhang, Peng Dai, Juwei Lu
State of the art (SOTA) few-shot learning (FSL) methods suffer significant performance drop in the presence of domain differences between source and target datasets.
no code implementations • 17 Feb 2021 • Avery Ma, Aladin Virmaux, Kevin Scaman, Juwei Lu
Do all adversarial examples have the same consequences?
no code implementations • ICCV 2021 • Xiheng Zhang, Yongkang Wong, Xiaofei Wu, Juwei Lu, Mohan Kankanhalli, Xiangdong Li, Weidong Geng
In this work, we take a step towards training robust models for cross-domain pose estimation task, which brings together ideas from causal representation learning and generative adversarial networks.
no code implementations • 1 Jan 2021 • Ali Ghobadzadeh, Deepak Sridhar, Juwei Lu, Wei Li
In this paper, we probe this direction by deriving a relationship between the estimation of unknown parameters of the probability density function (pdf) of input data and classification accuracy.
no code implementations • ECCV 2020 • Zhixiang Chi, Rasoul Mohammadi Nasiri, Zheng Liu, Juwei Lu, Jin Tang, Konstantinos N. Plataniotis
Recent advances in high refresh rate displays as well as the increased interest in high rate of slow motion and frame up-conversion fuel the demand for efficient and cost-effective multi-frame video interpolation solutions.