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<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
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<meta name="description" content="ECCV">
<meta property="og:title" content="ECCV2024"/>
<meta property="og:description" content="Stepping Stones: A Progressive Training Strategy for Audio-Visual Semantic Segmentation"/>
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<title>Stepping Stones</title>
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<h1 class="title is-1 publication-title">Stepping Stones: A Progressive Training Strategy for Audio-Visual Semantic Segmentation</h1>
<div class="is-size-5 publication-authors">
<!-- Paper authors -->
<span class="author-block">
<a href="https://github.com/ucasmjc" target="_blank">Juncheng Ma</a><sup>1</sup>,</span>
<span class="author-block">
<a href="SECOND AUTHOR PERSONAL LINK" target="_blank">Peiwen Sun</a><sup>2</sup>,</span>
<span class="author-block">
<a href="THIRD AUTHOR PERSONAL LINK" target="_blank">Yaoting Wang</a><sup>3</sup>,
</span>
<span class="author-block">
<a href="https://dtaoo.github.io/" target="_blank">Di Hu</a><sup>3,4*</sup>,
</span>
</div>
<div class="is-size-5 publication-authors">
<span class="author-block"><sup>1</sup>University of Chinese Academy of Sciences,
<br><sup>2</sup>Beijing University of Posts and Telecommunications,
<br><sup>3</sup>Gaoling School of Artificial Intelligence, Renmin University of China, China,
<br><sup>4</sup>Engineering Research Center of Next-Generation Search and Recommendation<br><strong>ECCV 2024</strong></span>
<span class="eql-cntrb"><small><br><sup>*</sup>Indicates Corresponding Author.</small></span>
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<span>Code</span>
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class="external-link button is-normal is-rounded is-dark">
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<span>arXiv</span>
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<h2 class="title is-3">Abstract</h2>
<div class="content has-text-justified">
<p>
Audio-Visual Segmentation (AVS) aims to achieve pixel-level localization of sound sources in videos, while Audio-Visual Semantic Segmentation (AVSS), as an extension of AVS, further pursues semantic understanding of audio-visual scenes. However, since the AVSS task requires the establishment of audio-visual correspondence and semantic understanding simultaneously, we observe that previous methods have struggled to handle this mashup of objectives in end-to-end training, resulting in insufficient learning and sub-optimization. Therefore, we propose a two-stage training strategy called Stepping Stones, which decomposes the AVSS task into two simple subtasks from localization to semantic understanding, which are fully optimized in each stage to achieve step-by-step global optimization. This training strategy has also proved its generalization and effectiveness on existing methods. To further improve the performance of AVS tasks, we propose a novel framework Adaptive Audio Visual Segmentation, in which we incorporate an adaptive audio query generator and integrate masked attention into the transformer decoder, facilitating the adaptive fusion of visual and audio features. Extensive experiments demonstrate that our methods achieve state-of-the-art results on all three AVS benchmarks..
</p>
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</section>
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<h2 class="title is-3 has-text-centered">Method</h2>
<img src="static/images/model.png" alt="MY ALT TEXT"/>
<br><br>
<h2 class="subtitle has-text-justified">
<p> Overview of AAVS framework. (1) Visual and audio features are extracted by the pre-trained encoder; (2) Adaptive Audio Query Generator is proposed to generate audio queries; (3) In the transformer decoder, audio-aware queries are integrated with visual feature maps, and masked cross-attention facilitates queries to dynamically adjust the attention range; (4) Finally, refined queries are merged with the mask feature to obtain the final prediction mask. <span style="color: red;">Red arrows</span> indicate newly introduced methods when implementing the \textit{Stepping Stones} strategy.
</p>
</h2>
</div>
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<h2 class="title is-3 has-text-centered">Quantitative Comparision</h2>
<img src="static/images/results.png" alt="MY ALT TEXT"/>
<br><br>
<h2 class="subtitle has-text-justified">
<p> Quantitative (mIoU, F-score) results on AVSBench dataset with transformer-based visual backbone. </p>
<p>* indicates that the model uses the <i>Stepping Stones</i> strategy.</p>
</h2>
</div>
</div>
</section>
<style>
.carousel {
display: flex;
justify-content: center; /* 水平居中 */
align-items: center; /* 垂直居中 */
}
.item {
text-align: center; /* 确保图片和文字在容器内居中 */
}
</style>
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<h2 class="title is-3 has-text-centered">Qualitative Comparision</h2>
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Qualitative comparison with previous methods on S4 subtask.
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Qualitative comparison with previous methods on MS3 subtask.
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Qualitative comparison with previous methods on AVSS subtask.
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<p> Video cases will be updated soon. </p>
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<section class="section" id="BibTeX">
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<h2 class="title">BibTeX</h2>
<pre><code>@article{ma2024steppingstones,
title={Stepping Stones: A Progressive Training Strategy for Audio-Visual Semantic Segmentation},
author={Ma, Juncheng and Sun, Peiwen and Wang, Yaoting and Hu, Di},
journal={IEEE European Conference on Computer Vision (ECCV)},
year={2024},
}</code></pre>
</div>
</section>
<!--End BibTex citation -->
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