1 code implementation • 16 May 2024 • Wentao Jiang, Jing Zhang, Di Wang, Qiming Zhang, Zengmao Wang, Bo Du
Experimental results in classification and dense prediction tasks show that LeMeViT has a significant $1. 7 \times$ speedup, fewer parameters, and competitive performance compared to the baseline models, and achieves a better trade-off between efficiency and performance.
1 code implementation • 14 Mar 2024 • Yuhang Zheng, Xiangyu Chen, Yupeng Zheng, Songen Gu, Runyi Yang, Bu Jin, Pengfei Li, Chengliang Zhong, Zengmao Wang, Lina Liu, Chao Yang, Dawei Wang, Zhen Chen, Xiaoxiao Long, Meiqing Wang
In particular, we propose an Efficient Feature Distillation (EFD) module that employs contrastive learning to efficiently and accurately distill language embeddings derived from foundational models.
no code implementations • 13 Mar 2024 • Long Lan, Fengxiang Wang, Shuyan Li, Xiangtao Zheng, Zengmao Wang, Xinwang Liu
Directly fine-tuning VLMs for RS-FGSC often encounters the challenge of overfitting the seen classes, resulting in suboptimal generalization to unseen classes, which highlights the difficulty in differentiating complex backgrounds and capturing distinct ship features.
no code implementations • 29 Feb 2024 • Boxuan Zhang, Zengmao Wang, Bo Du
The lack of object-level annotations poses a significant challenge for object detection in remote sensing images (RSIs).
no code implementations • 14 Apr 2022 • Wanyu Xu, Zengmao Wang, Wei Bian
Pseudo-labelling is a popular technique in unsuper-vised domain adaptation for semantic segmentation.
1 code implementation • CVPR 2022 • Ziyi Liu, Zengmao Wang, Bo Du
In this paper, we propose a deep protein subcellular localization method with multi-marginal contrastive learning to perceive the same PSLs in different tissue images and different PSLs within the same tissue image.
no code implementations • 14 Apr 2019 • Bo Du, Zengmao Wang, Lefei Zhang, Liangpei Zhang, Wei Liu, Jialie Shen, DaCheng Tao
Then can we find a way to fuse the two active sampling criteria without any assumption on data?
no code implementations • 14 Apr 2019 • Bo Du, Zengmao Wang, Lefei Zhang, Liangpei Zhang, DaCheng Tao
Meanwhile, it is also hard to build a good model without diagnosing discriminative labels.
no code implementations • 6 Mar 2018 • Xi Fang, Zengmao Wang, Xinyao Tang, Chen Wu
Simultaneously, our proposed method makes full use of the label information, and the proposed active learning is designed based on multiple classes.