no code implementations • 18 Apr 2024 • Xiaorui Qi, Qijie Bai, Yanlong Wen, Haiwei Zhang, Xiaojie Yuan
Specifically, we build three unique views, original, coarsening, and conversion, to learn a thorough structural representation.
1 code implementation • 6 Oct 2023 • Haiwei Zhang, Jiqing Zhang, Bo Dong, Pieter Peers, Wenwei Wu, Xiaopeng Wei, Felix Heide, Xin Yang
To the best of our knowledge, our method is the first eye-based emotion recognition method that leverages event-based cameras and spiking neural network.
1 code implementation • 19 May 2023 • Yu Zhao, Yike Wu, Xiangrui Cai, Ying Zhang, Haiwei Zhang, Xiaojie Yuan
Our approach captures the unified correlation pattern of two kinds of information between entities, and explicitly models the fine-grained interaction between original entity information.
1 code implementation • 14 Apr 2023 • Qijie Bai, JiaWen Guo, Haiwei Zhang, Changli Nie, Lin Zhang, Xiaojie Yuan
Temporal heterogeneous information network (temporal HIN) embedding, aiming to represent various types of nodes of different timestamps into low dimensional spaces while preserving structural and semantic information, is of vital importance in diverse real-life tasks.
1 code implementation • 14 Apr 2023 • Qijie Bai, Changli Nie, Haiwei Zhang, Dongming Zhao, Xiaojie Yuan
In this paper, we propose HGWaveNet, a novel hyperbolic graph neural network that fully exploits the fitness between hyperbolic spaces and data distributions for temporal link prediction.
no code implementations • ICCV 2023 • Yuxiang Cai, Yifan Zhu, Haiwei Zhang, Bo Ren
We compare the metrics on our dataset and SLAM reconstruction results in both synthetic scenes and real scenes with the previous methods.
1 code implementation • 17 Oct 2022 • Yu Zhao, Xiangrui Cai, Yike Wu, Haiwei Zhang, Ying Zhang, Guoqing Zhao, Ning Jiang
Based on these embeddings, in the inference phase, we first make modality-split predictions and then exploit various ensemble methods to combine the predictions with different weights, which models the modality importance dynamically.
no code implementations • CVPR 2022 • Wei Li, Haiwei Zhang, Qijie Bai, Guoqing Zhao, Ning Jiang, Xiaojie Yuan
However, the application value of SG on downstream tasks is severely limited by the predicate classification bias, which is caused by long-tailed data and presented as semantic bias of predicted relation predicates.
no code implementations • CVPR 2022 • Jiqing Zhang, Bo Dong, Haiwei Zhang, Jianchuan Ding, Felix Heide, BaoCai Yin, Xin Yang
In particular, the proposed architecture features a transformer module to provide global spatial information and a spiking neural network (SNN) module for extracting temporal cues.