no code implementations • 18 Dec 2023 • Jinxiang Lai, Wenlong Wu, Bin-Bin Gao, Jun Liu, Jiawei Zhan, Congchong Nie, Yi Zeng, Chengjie Wang
Image matching and object detection are two fundamental and challenging tasks, while many related applications consider them two individual tasks (i. e. task-individual).
no code implementations • 20 Apr 2023 • Jinxiang Lai, Siqian Yang, JunHong Zhou, Wenlong Wu, Xiaochen Chen, Jun Liu, Bin-Bin Gao, Chengjie Wang
According to this, we propose a novel Clustered-patch Element Connection (CEC) layer to correct the mismatch problem.
Ranked #48 on Few-Shot Semantic Segmentation on COCO-20i (5-shot)
1 code implementation • 15 Mar 2023 • Jinxiang Lai, Siqian Yang, Wenlong Wu, Tao Wu, Guannan Jiang, Xi Wang, Jun Liu, Bin-Bin Gao, Wei zhang, Yuan Xie, Chengjie Wang
Then we derive two specific attention modules, named SpatialFormer Semantic Attention (SFSA) and SpatialFormer Target Attention (SFTA), to enhance the target object regions while reduce the background distraction.
no code implementations • 2 Nov 2022 • Jinxiang Lai, Siqian Yang, Guannan Jiang, Xi Wang, Yuxi Li, Zihui Jia, Xiaochen Chen, Jun Liu, Bin-Bin Gao, Wei zhang, Yuan Xie, Chengjie Wang
In this paper, for the first time, we investigate the contributions of different distance metrics, and propose an adaptive fusion scheme, bringing significant improvements in few-shot classification.
1 code implementation • 2 Nov 2022 • Jinxiang Lai, Siqian Yang, Wenlong Liu, Yi Zeng, Zhongyi Huang, Wenlong Wu, Jun Liu, Bin-Bin Gao, Chengjie Wang
Few-Shot Learning (FSL) alleviates the data shortage challenge via embedding discriminative target-aware features among plenty seen (base) and few unseen (novel) labeled samples.
no code implementations • 8 Sep 2022 • Jinxiang Lai, Wenlong Liu, Jun Liu
Continual Learning (CL) focuses on developing algorithms with the ability to adapt to new environments and learn new skills.
1 code implementation • Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS 2022) 2022 • Bin-Bin Gao, Xiaochen Chen, Zhongyi Huang, Congchong Nie, Jun Liu, Jinxiang Lai, Guannan Jiang, Xi Wang, Chengjie Wang
This paper focus on few-shot object detection~(FSOD) and instance segmentation~(FSIS), which requires a model to quickly adapt to novel classes with a few labeled instances.
Ranked #3 on Few-Shot Object Detection on MS-COCO (1-shot)
1 code implementation • Pattern Recognition 2020 • Jinxiang Lai, Liang Lei, Kaiyuan Deng, Runming Yan, Yang Ruan, Zhou Jinyun
In the paper, a novel fast and robust template matching method named A-MNS based on Majority Neighbour Similarity (MNS) and the annulus projection transformation (APT) is proposed.