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27 changes: 22 additions & 5 deletions _bibliography/papers.bib
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Expand Up @@ -11,13 +11,12 @@ @inproceedings{Differentiated2021
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3474085.3475660},
doi = {10.1145/3474085.3475660},
abstract = {Directly deploying a trained multi-modal classifier to a new environment usually leads to poor performance due to the well-known domain shift problem. Existing multi-modal domain adaptation methods treated each modality equally and optimize the sub-models of different modalities synchronously. However, as observed in this paper, the degrees of domain shift in different modalities are usually diverse. We propose a novel Differentiated Learning framework to make use of the diversity between multiple modalities for more effective domain adaptation. Specifically, we model the classifiers of different modalities as a group of teacher/student sub-models, and a novel Prototype based Reliability Measurement is presented to estimate the reliability of the recognition results made by each sub-model on the target domain. More reliable results are then picked up as teaching materials for all sub-models in the group. Considering the diversity of different modalities, each sub-model performs the Asynchronous Curriculum Learning by choosing the teaching materials from easy to hard measured by itself. Furthermore, a reliability-aware fusion scheme is proposed to combine all optimized sub-models to support final decision. Comprehensive experiments based on three multi-modal datasets with different learning tasks have been conducted, which show the superior performance of our model while comparing with state-of-the-art multi-modal domain adaptation models.},
booktitle = {Proceedings of the 29th ACM International Conference on Multimedia},
pages = {1322–1330},
numpages = {9},
keywords = {multi-modal analysis, domain adaptation, differentiated learning},
series = {MM '21},
bibtex_show={true},
bibtex_show={false},
selected={true},
preview={dlmm.png}
}
Expand All @@ -31,8 +30,9 @@ @article{chen2021adversarial
pages={7079--7090},
year={2021},
publisher={IEEE},
bibtex_show={true},
preview={jm.png}
bibtex_show={false},
preview={jm.png},
pdf={Chen_Adversarial_Caching_Training.pdf}
}

@InProceedings{Liu_2025_CVPR,
Expand All @@ -42,11 +42,28 @@ @InProceedings{Liu_2025_CVPR
month = {June},
year = {2025},
pages = {5092-5101},
bibtex_show={true},
bibtex_show={false},
selected={true},
preview={cvpr25_poster_1035_00.png},
pdf={Liu_MODfinity_Unsupervised_Domain_Adaptation_with_Multimodal_Information_Flow_Intertwining_CVPR_2025_paper.pdf}
}

@article{Jie_2025,
title={FS-Diff: Semantic guidance and clarity-aware simultaneous multimodal image fusion and super-resolution},
volume={121},
ISSN={1566-2535},
url={http://dx.doi.org/10.1016/j.inffus.2025.103146},
DOI={10.1016/j.inffus.2025.103146},
journal={Information Fusion},
publisher={Elsevier BV},
author={Jie, Yuchan and Xu, Yushen and Li, Xiaosong and Zhou, Fuqiang and Lv, Jianming and Li, Huafeng},
year={2025},
month=sep,
pages={103146},
preview={Jie_FS-Diff.jpg},
pdf={Jie_FS-Diff.pdf}
}

article{PhysRev.47.777,
使用示例:
preview 加入预览的图片,预览的图片放在 `assets/img/publication_preview/` 目录下
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34 changes: 14 additions & 20 deletions _pages/about.md
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Expand Up @@ -59,22 +59,21 @@ selected_papers: false # includes a list of papers marked as "selected={true}"
line-height: 1.8;
}

/* 轮播图样式 - 增加高度 */
.carousel-showcase {
margin: 25px 0;
border-radius: 12px;
overflow: hidden;
box-shadow: 0 8px 20px rgba(0,0,0,0.12);
height: 600px; /* 从380px增加到600px */
height: 600px;
}
.carousel-item {
height: 600px; /* 同步增加 */
height: 600px;
}
.carousel-item img {
width: 100%;
height: 100%;
object-fit: contain; /* 改为contain确保完整显示 */
background-color: #f8f9fa; /* 添加背景色避免空白 */
object-fit: contain;
background-color: #f8f9fa;
}
.carousel-caption {
background: linear-gradient(to top, rgba(0,0,0,0.8), transparent);
Expand Down Expand Up @@ -118,19 +117,15 @@ selected_papers: false # includes a list of papers marked as "selected={true}"
<div class="lab-card">
<h2><i class="fas fa-flask"></i> 实验室简介</h2>

<!-- 修改轮播容器,移除 data-bs-ride="carousel" -->
<div id="labCarousel" class="carousel slide carousel-showcase">
<!-- 轮播指示器保持不变 -->
<div class="carousel-indicators">
<button type="button" data-bs-target="#labCarousel" data-bs-slide-to="0" class="active"></button>
<button type="button" data-bs-target="#labCarousel" data-bs-slide-to="1"></button>
<button type="button" data-bs-target="#labCarousel" data-bs-slide-to="2"></button>
<!-- 添加第4、5张的指示器 -->
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<button type="button" data-bs-target="#labCarousel" data-bs-slide-to="4"></button>
</div>

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<div class="carousel-inner">
<div class="carousel-item active">
<img src="assets/img/intro1.png" class="d-block w-100" alt="intro1">
Expand All @@ -149,7 +144,6 @@ selected_papers: false # includes a list of papers marked as "selected={true}"
</div>
</div>

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<button class="carousel-control-prev" type="button" data-bs-target="#labCarousel" data-bs-slide="prev">
<span class="carousel-control-prev-icon"></span>
</button>
Expand All @@ -158,7 +152,7 @@ selected_papers: false # includes a list of papers marked as "selected={true}"
</button>
</div>

<p>本实验室聚焦人工智能前沿领域,致力于多模态深度学习的核心技术研究与应用创新。团队重点攻关跨模态信息融合与鲁棒特征学习,在计算机视觉与信号处理领域取得突破性进展。</p>
<!-- <p>本实验室聚焦人工智能前沿领域,致力于多模态深度学习的核心技术研究与应用创新。团队重点攻关跨模态信息融合与鲁棒特征学习,在计算机视觉与信号处理领域取得突破性进展。</p> -->
</div>

<!-- <script>
Expand All @@ -183,26 +177,26 @@ document.addEventListener('DOMContentLoaded', function() {
</div>
<!-- 研究方向1 -->
<div style="background-color: transparent; border-radius: 12px; padding: 25px; margin-bottom: 25px; box-shadow: 0 5px 15px rgba(0,0,0,0.06); display: flex; align-items: center;">
<div style="background: #3498db; color: white; width: 70px; height: 70px; border-radius: 50%; display: flex; align-items: center; justify-content: center; margin-right: 20px; flex-shrink: 0; font-size: 1.8rem; font-weight: bold;">1</div>
<div style="background: #e74c3c; color: white; width: 70px; height: 70px; border-radius: 50%; display: flex; align-items: center; justify-content: center; margin-right: 20px; flex-shrink: 0; font-size: 1.8rem; font-weight: bold;">1</div>
<div>
<h3 style=" margin-top: 0;">图像去噪与增强</h3>
<p>研发新一代基于深度学习的图像复原算法,针对低光照、医学影像、遥感图像等复杂场景,实现高保真噪声抑制与细节重建。</p>
<h3 style=" margin-top: 0;">弹性记忆网络(EMN)架构创新</h3>
<p>首创时空高效的弹性记忆网络框架,通过参数压缩与映射的创新架构,在保持模型精度的同时,大幅模型提升推理速度,显著降低硬件资源消耗。</p>
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<div style="background-color: transparent; border-radius: 12px; padding: 25px; margin-bottom: 25px; box-shadow: 0 5px 15px rgba(0,0,0,0.06); display: flex; align-items: center;">
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<div style="background: #27ae60; color: white; width: 70px; height: 70px; border-radius: 50%; display: flex; align-items: center; justify-content: center; margin-right: 20px; flex-shrink: 0; font-size: 1.8rem; font-weight: bold;">2</div>
<div>
<h3 style=" margin-top: 0;">弹性记忆网络(EMN)架构创新</h3>
<p>首创时空高效的弹性记忆网络框架,通过参数压缩与映射的创新架构,在保持模型精度的同时,大幅模型提升推理速度,显著降低硬件资源消耗。</p>
<h3 style=" margin-top: 0;">多模态协同学习</h3>
<p>探索视觉-语言-音频的联合表示学习,构建跨模态自监督预训练模型,为智能医疗诊断、工业质检、自动驾驶等场景提供统一感知解决方案。</p>
</div>
</div>
<!-- 研究方向3 -->
<div style="background-color: transparent; border-radius: 12px; padding: 25px; margin-bottom: 25px; box-shadow: 0 5px 15px rgba(0,0,0,0.06); display: flex; align-items: center;">
<div style="background: #27ae60; color: white; width: 70px; height: 70px; border-radius: 50%; display: flex; align-items: center; justify-content: center; margin-right: 20px; flex-shrink: 0; font-size: 1.8rem; font-weight: bold;">3</div>
<div style="background: #3498db; color: white; width: 70px; height: 70px; border-radius: 50%; display: flex; align-items: center; justify-content: center; margin-right: 20px; flex-shrink: 0; font-size: 1.8rem; font-weight: bold;">3</div>
<div>
<h3 style=" margin-top: 0;">多模态协同学习</h3>
<p>探索视觉-语言-音频的联合表示学习,构建跨模态自监督预训练模型,为智能医疗诊断、工业质检、自动驾驶等场景提供统一感知解决方案。</p>
<h3 style=" margin-top: 0;">图像去噪与增强</h3>
<p>研发新一代基于深度学习的图像复原算法,针对低光照、医学影像、遥感图像等复杂场景,实现高保真噪声抑制与细节重建。</p>
</div>
</div>
<!-- 研究成果 -->
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5 changes: 4 additions & 1 deletion _projects/HeXuyi.md
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Expand Up @@ -2,7 +2,7 @@
layout: page
title: 何旭怡
description: 25级在读博士
img: assets/img/hxy.jpg
img: assets/img/hxy2.jpg
importance: 2025
category: Current students
related_publications: false
Expand Down Expand Up @@ -47,6 +47,9 @@ related_publications: false
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{% include figure.liquid loading="eager" path="assets/img/hxy1.jpg" title="生活照片" class="img-fluid rounded z-depth-1" %}
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{% include figure.liquid loading="eager" path="assets/img/hxy.jpg" title="生活照片" class="img-fluid rounded z-depth-1" %}
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<!-- 底部学校信息 -->
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69 changes: 69 additions & 0 deletions _projects/WangChengjun.md
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@@ -0,0 +1,69 @@
---
layout: page
title: 王铖俊
description: 24级在读博士
img: assets/img/lsl.jpg
importance: 2024
category: Current students
related_publications: false
---

<div class="row justify-content-sm-center">
<div class="col-sm-8 mt-3 mt-md-0">
<!-- 个人信息 -->
<div style="margin-bottom: 30px;">
<h4 style="color: #1a6fc4; margin-bottom: 10px;">个人信息</h4>
<p style="margin: 8px 0;"><strong>硕士院校:</strong>河北大学</p>
</div>
<!-- 联系信息 -->
<div style="margin-bottom: 30px;">
<h4 style="color: #1a6fc4; margin-bottom: 10px;">联系方式</h4>
<p style="margin: 8px 0;"><strong>电子邮箱:</strong>[email protected]</p>
</div>
<!-- 研究方向 -->
<div style="margin-bottom: 30px;">
<h4 style="color: #1a6fc4; margin-bottom: 10px;">研究方向</h4>
<p style="margin: 5px 0;">多模态、持续学习</p>
</div>
</div>
<div class="col-sm-4 mt-3 mt-md-0">
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<h4 style="color: #1a6fc4; margin-bottom: 10px;">个人成果</h4>
<div style="margin-bottom: 15px; padding: 12px; border-left: 4px solid #3498db; background-color: transparent; box-shadow: 0 2px 4px rgba(0,0,0,0.1);">
<span style="font-weight: bold; color: #e74c3c;">[1]</span> Wang C, Peng J, Tao Z, et al. Uncertainty-guided Robust labels refinement for unsupervised person re-identification. <span style="font-style: italic; color: #2980b9;">Neural Comput & Applic</span> 36, 977–991 (2024).
<span style="font-weight: bold; color: #e74c3c;">[2]</span> Peng J, Yu J, Wang C, et al. Adapt only once: Fast unsupervised person re-identification via relevance-aware guidance <span style="font-style: italic; color: #2980b9;">Pattern Recognition</span> 150, 110360 (2024).
<span style="font-weight: bold; color: #e74c3c;">[3]</span> Zhang S, Wang C, Peng J. ABC-Learning: Attention-Boosted Contrastive Learning for unsupervised person re-identification <span style="font-style: italic; color: #2980b9;">Engineering Applications of Artificial Intelligence</span> 133, 108344 (2024).
</div>

<h4 style="color: #1a6fc4; margin-bottom: 10px;">学生风采</h4>
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<!-- 底部学校信息 -->
<div style="margin-top: 25px; text-align: center; color: #777; font-size: 14px; border-top: 1px solid #eee; padding-top: 15px;">
华南理工大学
</div>
12 changes: 6 additions & 6 deletions _projects/YaoYiyang.md
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layout: page
title: 姚一阳
description: 25级在读博士
img: assets/img/lsl.jpg
img: assets/img/yyy.jpg
importance: 2025
category: Current students
related_publications: false
Expand Down Expand Up @@ -39,25 +39,25 @@ related_publications: false
<h4 style="color: #1a6fc4; margin-bottom: 10px;">学生风采</h4>
<div class="row">
<div class="col-sm mt-3 mt-md-0">
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