1 code implementation • 11 Dec 2024 • Huafeng Li, Dayong Su, Qing Cai, Yafei Zhang
To address this challenge, this paper proposes an unaligned medical image fusion method called Bidirectional Stepwise Feature Alignment and Fusion (BSFA-F) strategy.
1 code implementation • 26 Nov 2024 • Mengzhao Wang, Huafeng Li, Yafei Zhang, Jinxing Li, Minghong Xie, Dapeng Tao
The retrieval branch uses inter-video contrastive learning to roughly align the global features of paragraphs and videos, reducing modality differences and constructing a coarse-grained feature space to break free from the need for correspondence between paragraphs and videos.
no code implementations • 16 Nov 2024 • Huafeng Li, Jiaqi Fang, Yafei Zhang, Yu Liu
To address this, we propose a joint learning framework that utilizes infrared image for the restoration and fusion of hazy IR-VIS images.
no code implementations • 14 Nov 2024 • Zengyi Yang, Yafei Zhang, Huafeng Li, Yu Liu
The primary value of infrared and visible image fusion technology lies in applying the fusion results to downstream tasks.
1 code implementation • 31 Oct 2024 • Minghong Xie, Mengzhao Wang, Huafeng Li, Yafei Zhang, Dapeng Tao, Zhengtao Yu
In addition, a corresponding target object position progressive correction strategy is defined based on the hierarchical matching mechanism to achieve accurate positioning for the target object described in the text.
1 code implementation • 27 Jul 2024 • Xiaoyan Yu, Shen Zhou, Huafeng Li, Liehuang Zhu
However, several practical challenges remain, including meeting the specific and simultaneous demands of different tasks, balancing relationships between tasks, and effectively utilizing task correlations in model design.
1 code implementation • 7 Mar 2024 • Huafeng Li, Zhenmei Yang, Yafei Zhang, Dapeng Tao, Zhengtao Yu
This network, comprising single-frame HDR reconstruction with enhanced stop image (SHDR-ESI) and SHDR-ESI-assisted multi-exposure HDR reconstruction (SHDRA-MHDR), effectively leverages the ghost-free characteristic of single-frame HDR reconstruction and the detail-enhancing capability of ESI in oversaturated areas.
1 code implementation • CVPR 2024 • Yafei Zhang, Shen Zhou, Huafeng Li
On the one hand, the difference perception between the depth maps of the dehazing result and the ideal image is proposed to promote the dehazing network to pay attention to the non-ideal areas of the dehazing.
1 code implementation • 3 Feb 2024 • Xilai Li, Wuyang Liu, Xiaosong Li, Fuqiang Zhou, Huafeng Li, Feiping Nie
For the restoration module, we propose a physically-aware clear feature prediction module based on an atmospheric scattering model that can deduce variations in light transmittance from both scene illumination and reflectance.
1 code implementation • 12 Sep 2023 • Keying Du, Huafeng Li, Yafei Zhang, Zhengtao Yu
Specifically, to skillfully sidestep aggregating complementary information in IVIF, we design a mutual information transfer (MIT) module to mutually represent features from two modalities, roughly transferring complementary information into harmonious one.
no code implementations • 9 Sep 2023 • Huafeng Li, Dan Wang, Yuxin Huang, Yafei Zhang, Zhengtao Yu
To distinguish the hard pixels from the source images, we achieve the determination of hard pixels by considering the inconsistency among the detection results of focus areas in source images.
no code implementations • 23 Aug 2023 • Huafeng Li, Shedan Yang, Yafei Zhang, Dapeng Tao, Zhengtao Yu
In addition, to further reduce the negative impact of modal discrepancy and text diversity on cross-modal matching, we propose to use other sample knowledge of the same modality, i. e., external knowledge to enhance identity-consistent features and weaken identity-inconsistent features.
1 code implementation • 22 Jul 2023 • Yafei Zhang, Zhiyuan Li, Huafeng Li, Dapeng Tao
To this end, a multi-modal MR brain tumor segmentation method with tumor prototype-driven and multi-expert integration is proposed.
no code implementations • 13 Jul 2023 • Huafeng Li, Yanmei Mao, Yafei Zhang, Guanqiu Qi, Zhengtao Yu
Therefore, the supervised model training is achieved under the style supervision of the target domain by exchanging styles between source-domain samples and target-domain samples, and the challenges caused by the lack of cross-camera paired samples are solved by utilizing cross-camera similar samples.
Domain Adaptive Person Re-Identification
Person Re-Identification
no code implementations • 8 Jul 2023 • Huafeng Li, Le Xu, Yafei Zhang, Dapeng Tao, Zhengtao Yu
In this work, the changes of views, posture, background and modal discrepancy are considered as the main factors that cause the perturbations of person identity features.
1 code implementation • 16 Nov 2022 • Fan Li, Hang Zhou, Huafeng Li, Yafei Zhang, Zhengtao Yu
Specifically, we improve the interpretability of text features by providing them with consistent semantic information with image features to achieve the alignment of text and describe image region features. To address the challenges posed by the diversity of text and the corresponding person images, we treat the variation caused by diversity to features as caused by perturbation information and propose a novel adversarial attack and defense method to solve it.
1 code implementation • CVPR 2022 • Xinyu Lin, Jinxing Li, Zeyu Ma, Huafeng Li, Shuang Li, Kaixiong Xu, Guangming Lu, David Zhang
Based on our constructed dataset, we prove that with the increase of frames in a tracklet, the performance does meet more enhancement, demonstrating the significance of video-to-video matching in RGB-IR person Re-ID.
1 code implementation • 26 Jun 2021 • Huafeng Li, Kaixiong Xu, Jinxing Li, Guangming Lu, Yong Xu, Zhengtao Yu, David Zhang
Since human-labeled samples are free for the target set, unsupervised person re-identification (Re-ID) has attracted much attention in recent years, by additionally exploiting the source set.
1 code implementation • 22 Apr 2021 • Jian Pang, Dacheng Zhang, Huafeng Li, Weifeng Liu, Zhengtao Yu
This paper proposes a novel Interference Suppression Model (ISM) to deal with the interference caused by the hazy weather in domain adaptation person Re-ID.
no code implementations • 16 Jul 2017 • Meng Wang, Huafeng Li, Fang Li
The GANs promote an adversarive game to approximate complex and jointed example probability.