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 • 7 Nov 2023 • Direnc Pekaslan, Jose Maria Alonso-Moral, Kasun Bandara, Christoph Bergmeir, Juan Bernabe-Moreno, Robert Eigenmann, Nils Einecke, Selvi Ergen, Rakshitha Godahewa, Hansika Hewamalage, Jesus Lago, Steffen Limmer, Sven Rebhan, Boris Rabinovich, Dilini Rajapasksha, Heda Song, Christian Wagner, Wenlong Wu, Luis Magdalena, Isaac Triguero
These competitions focus on accurate energy consumption forecasting and the importance of interpretability in understanding the underlying factors.
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 • 23 Nov 2022 • Jiawei Zhan, Jun Liu, Wei Tang, Guannan Jiang, Xi Wang, Bin-Bin Gao, Tianliang Zhang, Wenlong Wu, Wei zhang, Chengjie Wang, Yuan Xie
This paper builds a unified framework to perform effective noisy-proposal suppression and to interact between global and local features for robust feature learning.
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.
1 code implementation • CVPR 2023 • Dihe Huang, Ying Chen, Shang Xu, Yong liu, Wenlong Wu, Yikang Ding, Chengjie Wang, Fan Tang
The detector-free feature matching approaches are currently attracting great attention thanks to their excellent performance.
no code implementations • 1 Oct 2020 • Wenlong Wu, James M. Keller, Jeffrey Dale, James C. Bezdek
Incoming data is normally assigned a crisp label (into one of the structures) and that structure's footprint is incrementally updated.