1 code implementation • 29 Feb 2024 • Feng Lu, Xiangyuan Lan, Lijun Zhang, Dongmei Jiang, YaoWei Wang, Chun Yuan
Over the past decade, most methods in visual place recognition (VPR) have used neural networks to produce feature representations.
1 code implementation • 25 Feb 2024 • Feng Lu, Shuting Dong, Lijun Zhang, Bingxi Liu, Xiangyuan Lan, Dongmei Jiang, Chun Yuan
Moreover, we design a re-projection error of inliers loss to train the DHE network without additional homography labels, which can also be jointly trained with the backbone network to help it extract the features that are more suitable for local matching.
1 code implementation • 22 Feb 2024 • Feng Lu, Lijun Zhang, Xiangyuan Lan, Shuting Dong, YaoWei Wang, Chun Yuan
Experimental results show that our method outperforms the state-of-the-art methods with less training data and training time, and uses about only 3% retrieval runtime of the two-stage VPR methods with RANSAC-based spatial verification.
Ranked #1 on Visual Place Recognition on Pittsburgh-250k-test
1 code implementation • ICCV 2023 • Guiping Cao, Shengda Luo, Wenjian Huang, Xiangyuan Lan, Dongmei Jiang, YaoWei Wang, JianGuo Zhang
Finally, based on the Strip MLP layer, we propose a novel \textbf{L}ocal \textbf{S}trip \textbf{M}ixing \textbf{M}odule (LSMM) to boost the token interaction power in the local region.
1 code implementation • 3 Apr 2023 • Qinglin Liu, Xiaoqian Lv, Quanling Meng, Zonglin Li, Xiangyuan Lan, Shuo Yang, Shengping Zhang, Liqiang Nie
Furthermore, AEMatter leverages a large image training strategy to assist the network in learning context aggregation from data.
Ranked #1 on Image Matting on Composition-1K
no code implementations • 22 Mar 2021 • Chunzhi Yi, Feng Jiang, Shengping Zhang, Hao Guo, Chifu Yang, Zhen Ding, Baichun Wei, Xiangyuan Lan, Huiyu Zhou
Challenges of exoskeletons motor intent decoding schemes remain in making a continuous prediction to compensate for the hysteretic response caused by mechanical transmission.
no code implementations • 12 Jan 2021 • Xuanyu He, Wei zhang, Ran Song, Qian Zhang, Xiangyuan Lan, Lin Ma
By studying two unsupervised person re-ID methods in a cross-method way, we point out a hard negative problem is handled implicitly by their designs of data augmentations and PK sampler respectively.
1 code implementation • 25 Nov 2019 • Rui Shao, Xiangyuan Lan, Pong C. Yuen
Besides, to further enhance the generalization ability of our model, the proposed framework adopts a fine-grained learning strategy that simultaneously conducts meta-learning in a variety of domain shift scenarios in each iteration.
no code implementations • 6 Jun 2019 • Zheheng Jiang, Zhihua Liu, Long Chen, Lei Tong, Xiangrong Zhang, Xiangyuan Lan, Danny Crookes, Ming-Hsuan Yang, Huiyu Zhou
The study of mouse social behaviours has been increasingly undertaken in neuroscience research.
no code implementations • ECCV 2018 • Si-Qi Liu, Xiangyuan Lan, Pong C. Yuen
3D mask face presentation attack, as a new challenge in face recognition, has been attracting increasing attention.
no code implementations • ECCV 2018 • Mang Ye, Xiangyuan Lan, Pong C. Yuen
After that, a robust and efficient top-k counts label prediction strategy is proposed to predict the labels of unlabeled image sequences.
Ranked #11 on Person Re-Identification on PRID2011
Representation Learning Video-Based Person Re-Identification
no code implementations • CVPR 2014 • Xiangyuan Lan, Andy J. Ma, Pong C. Yuen
The use of multiple features for tracking has been proved as an effective approach because limitation of each feature could be compensated.