no code implementations • 28 Mar 2024 • Hao Shen, Lu Shi, Wanru Xu, Yigang Cen, Linna Zhang, Gaoyun An
To mitigate memory consumption, we convert the order information prediction task into a multi-label learning problem, and the inter-patch similarity prediction task into a distance matrix regression problem.
1 code implementation • 16 Mar 2024 • Shichao Kan, Yuhai Deng, Yixiong Liang, Lihui Cen, Zhe Qu, Yigang Cen, Zhihai He
This paper presents a novel unsupervised deep metric learning approach, termed unsupervised collaborative metric learning with mixed-scale groups (MS-UGCML), devised to learn embeddings for objects of varying scales.
1 code implementation • 26 Mar 2023 • Yue Zhang, Suchen Wang, Shichao Kan, Zhenyu Weng, Yigang Cen, Yap-Peng Tan
Our key idea is to formulate the POAR problem as an image-text search problem.
1 code implementation • 10 Oct 2022 • Shichao Kan, Zhiquan He, Yigang Cen, Yang Li, Vladimir Mladenovic, Zhihai He
Recent methods for deep metric learning have been focusing on designing different contrastive loss functions between positive and negative pairs of samples so that the learned feature embedding is able to pull positive samples of the same class closer and push negative samples from different classes away from each other.
no code implementations • 9 Oct 2022 • Shichao Kan, Yixiong Liang, Min Li, Yigang Cen, Jianxin Wang, Zhihai He
To address this challenge, in this paper, we introduce a new method called coded residual transform (CRT) for deep metric learning to significantly improve its generalization capability.
no code implementations • 13 Feb 2022 • Xu Wang, Yi Jin, Yigang Cen, Tao Wang, Bowen Tang, Yidong Li
Compared with traditional task-irrelevant downsampling methods, task-oriented neural networks have shown improved performance in point cloud downsampling range.
no code implementations • CVPR 2021 • Shichao Kan, Yigang Cen, Yang Li, Vladimir Mladenovic, Zhihai He
During training, this relative order prediction network and the feature embedding network are tightly coupled, providing mutual constraints to each other to improve overall metric learning performance in a cooperative manner.
no code implementations • 22 Feb 2021 • Xu Wang, Yi Jin, Yigang Cen, Tao Wang, Yidong Li
Recently, the advancement of 3D point clouds in deep learning has attracted intensive research in different application domains such as computer vision and robotic tasks.
no code implementations • 19 Feb 2021 • Shichao Kan, Yue Zhang, Fanghui Zhang, Yigang Cen
Based on the atmospheric scattering model, a novel model is designed to directly generate the haze-free image.
no code implementations • 25 Apr 2018 • Zhi Zhang, Guanghan Ning, Yigang Cen, Yang Li, Zhiqun Zhao, Hao Sun, Zhihai He
The inference structures and computational complexity of existing deep neural networks, once trained, are fixed and remain the same for all test images.