no code implementations • 7 May 2024 • Jinke Li, Xiao He, Chonghua Zhou, Xiaoqiang Cheng, Yang Wen, Dan Zhang
Leveraging the proposed view attention as well as an additional multi-frame streaming temporal attention, we introduce ViewFormer, a vision-centric transformer-based framework for spatiotemporal feature aggregation.
no code implementations • 19 Mar 2024 • Shijin Chen, Zeyi Liu, Xiao He, Dongliang Zou, Donghua Zhou
The gearbox is a critical component of electromechanical systems.
1 code implementation • 14 Feb 2024 • Zhaoqing Wang, Xiaobo Xia, Ziye Chen, Xiao He, Yandong Guo, Mingming Gong, Tongliang Liu
With this unpaired mask-text supervision, we propose a new weakly-supervised open-vocabulary segmentation framework (Uni-OVSeg) that leverages confident pairs of mask predictions and entities in text descriptions.
no code implementations • 8 Oct 2023 • Yan Zhang, Hao Hao, Xiao He, Shuanhu Gao, Aimin Zhou
The experimental results show that, in comparison to the Monte Carlo tree search algorithm, EA significantly reduces the number of calling single-step model by an average of 53. 9%.
no code implementations • 11 Sep 2023 • Xiao He, Mingrui Zhu, Dongxin Chen, Nannan Wang, Xinbo Gao
In this paper, we unify the task of anonymization and visual identity information hiding and propose a novel face privacy protection method based on diffusion models, dubbed Diff-Privacy.
1 code implementation • 14 Jun 2023 • Xiao He, Chang Tang, Xinwang Liu, Wei zhang, Kun Sun, Jiangfeng Xu
S2ADet comprises a hyperspectral information decoupling (HID) module, a two-stream feature extraction network, and a one-stage detection head.
1 code implementation • 29 Apr 2023 • Chen Li, Zeyi Liu, LiMin Wang, Minyue Li, Xiao He
Fault diagnosis is a crucial area of research in industry.
2 code implementations • 25 Apr 2023 • Zeyi Liu, Songqiao Hu, Xiao He
In this paper, a review of methods and techniques for RTSA tasks in non-stationary environments is provided.
1 code implementation • 4 Apr 2023 • Xiao He, Ye Li, Jian Tan, Bin Wu, Feifei Li
Extensive experiments on real-world benchmark datasets for downstream time series anomaly detection and forecasting tasks demonstrate that OneShotSTL is from 10 to over 1, 000 times faster than the state-of-the-art methods, while still providing comparable or even better accuracy.
no code implementations • 25 Mar 2023 • Songqiao Hu, Zeyi Liu, Xiao He
When a new data chunk arrives, we use both real labels and pseudo labels to update the model after prediction and drift detection.
no code implementations • 24 Jan 2023 • Xiao He, Mingrui Zhu, Nannan Wang, Xinbo Gao, Heng Yang
To address this issue, we propose a novel font generation approach by learning the Difference between different styles and the Similarity of the same style (DS-Font).
no code implementations • ICCV 2023 • Mingrui Zhu, Xiao He, Nannan Wang, Xiaoyu Wang, Xinbo Gao
In this paper, we propose a novel all-to-key attention mechanism -- each position of content features is matched to stable key positions of style features -- that is more in line with the characteristics of style transfer.
no code implementations • CVPR 2022 • Jinke Li, Xiao He, Yang Wen, Yuan Gao, Xiaoqiang Cheng, Dan Zhang
As a rising task, panoptic segmentation is faced with challenges in both semantic segmentation and instance segmentation.
no code implementations • 14 May 2020 • Yinghong Zhao, Xiao He, Donghua Zhou, Michael G. Pecht
Different from the existing moving average (MA) technique that puts an equal weight on samples within a time window, WMA uses correlation information to find an optimal weight vector (OWV), so as to better improve the index's robustness and sensitivity.
2 code implementations • 28 Mar 2019 • Luca Franceschi, Mathias Niepert, Massimiliano Pontil, Xiao He
With this work, we propose to jointly learn the graph structure and the parameters of graph convolutional networks (GCNs) by approximately solving a bilevel program that learns a discrete probability distribution on the edges of the graph.
Ranked #3 on Node Classification on Cora: fixed 20 node per class
no code implementations • 14 Nov 2018 • Xiao He, Francesco Alesiani, Ammar Shaker
Scaling up MTL methods to problems with a tremendous number of tasks is a big challenge.
no code implementations • 14 Feb 2018 • Xiao He, Luis Moreira-Matias
Clustering consists of grouping together samples giving their similar properties.