1 code implementation • 13 Jul 2022 • Bo Pang, Yifan Zhang, Yaoyi Li, Jia Cai, Cewu Lu
In this paper, we propose a genuine group-level contrastive visual representation learning method whose linear evaluation performance on ImageNet surpasses the vanilla supervised learning.
Ranked #38 on Self-Supervised Image Classification on ImageNet
no code implementations • 11 Feb 2022 • Guanglong Xu, Zhensheng Hu, Jia Cai
Zero-shot sketch-based image retrieval (ZSSBIR), as a popular studied branch of computer vision, attracts wide attention recently.
no code implementations • 4 Dec 2021 • Zhilong Xiong, Jia Cai
Graph convolutional networks (GCNs) have achieved remarkable learning ability for dealing with various graph structural data recently.
no code implementations • 16 Nov 2021 • Jia Cai, Zhilong Xiong, Shaogao Lv
Graph convolutional network (GCN) is a powerful model studied broadly in various graph structural data learning tasks.
2 code implementations • 23 Oct 2020 • Kun Fang, Qinghua Tao, Yingwen Wu, Tao Li, Jia Cai, Feipeng Cai, Xiaolin Huang, Jie Yang
In this way, the proposed DIO augments the model and enhances the robustness of DNN itself as the learned features can be corrected by these mutually-orthogonal paths.
no code implementations • 23 Apr 2020 • Jia Cai, Kexin Lv, Junyi Huo, Xiaolin Huang, Jie Yang
To overcome this limitation, in this paper, we propose a sparse generalized canonical correlation analysis (GCCA), which could detect the latent relations of multiview data with sparse structures.
no code implementations • 4 Mar 2020 • Chengjin Sun, Sizhe Chen, Jia Cai, Xiaolin Huang
To implement the Type I attack, we destroy the original one by increasing the distance in input space while keeping the output similar because different inputs may correspond to similar features for the property of deep neural network.