no code implementations • 2 Feb 2024 • Xingtong Yu, Yuan Fang, Zemin Liu, Yuxia Wu, Zhihao Wen, Jianyuan Bo, Xinming Zhang, Steven C. H. Hoi
Finally, we outline prospective future directions for few-shot learning on graphs to catalyze continued innovation in this field.
no code implementations • 4 Dec 2023 • Xingtong Yu, Yuan Fang, Zemin Liu, Xinming Zhang
In this paper, we propose HGPROMPT, a novel pre-training and prompting framework to unify not only pre-training and downstream tasks but also homogeneous and heterogeneous graphs via a dual-template design.
1 code implementation • 28 Nov 2023 • Xingtong Yu, Chang Zhou, Yuan Fang, Xinming Zhang
Hence, in this paper, we propose MultiGPrompt, a novel multi-task pre-training and prompting framework to exploit multiple pretext tasks for more comprehensive pre-trained knowledge.
2 code implementations • 26 Nov 2023 • Xingtong Yu, Zhenghao Liu, Yuan Fang, Zemin Liu, Sihong Chen, Xinming Zhang
In this paper, we propose GraphPrompt, a novel pre-training and prompting framework on graphs.
1 code implementation • 16 Sep 2023 • Wenyu Zhang, Xin Deng, Baojun Jia, Xingtong Yu, Yifan Chen, Jin Ma, Qing Ding, Xinming Zhang
Additionally, we introduce the MLP-based Sequential Residual Block (MSRB) for robust feature extraction from text images, and a Local Contour Awareness loss ($\mathcal{L}_{lca}$) to enhance the model's perception of details.
2 code implementations • 16 Feb 2023 • Zemin Liu, Xingtong Yu, Yuan Fang, Xinming Zhang
In particular, prompting is a popular alternative to fine-tuning in natural language processing, which is designed to narrow the gap between pre-training and downstream objectives in a task-specific manner.
1 code implementation • 7 Feb 2023 • Xingtong Yu, Zemin Liu, Yuan Fang, Xinming Zhang
However, typical GNNs employ a node-centric message passing scheme that receives and aggregates messages on nodes, which is inadequate in complex structure matching for isomorphism counting.
no code implementations • CVPR 2023 • Xin Deng, Wenyu Zhang, Qing Ding, Xinming Zhang
In point cloud analysis, point-based methods have rapidly developed in recent years.
Ranked #1 on 3D Semantic Segmentation on OpenTrench3D
no code implementations • 29 Sep 2021 • Xingtong Yu, Zemin Liu, Yuan Fang, Xinming Zhang
At the graph level, we modulate the graph representation conditioned on the query subgraph, so that the model can be adapted to each unique query for better matching with the input graph.
no code implementations • ICCV 2021 • Zhi Chen, Xiaoqing Ye, Wei Yang, Zhenbo Xu, Xiao Tan, Zhikang Zou, Errui Ding, Xinming Zhang, Liusheng Huang
Second, we introduce an occlusion-aware distillation (OA Distillation) module, which leverages the predicted depths from StereoNet in non-occluded regions to train our monocular depth estimation network named SingleNet.
no code implementations • 2 Nov 2020 • Nan Lin, YuXuan Li, Yujun Zhu, Ruolin Wang, Xiayu Zhang, Jianmin Ji, Keke Tang, Xiaoping Chen, Xinming Zhang
Our meta policy tries to manipulate the next optimal state and actual action is produced by the inverse dynamics model.
no code implementations • 28 Nov 2017 • Di Yuan, Xiaohuan Lu, Donghao Li, Yingyi Liang, Xinming Zhang
Most of the correlation filter based tracking algorithms can achieve good performance and maintain fast computational speed.