Wodlinger, M., Kotera, J., Keglevic, M., Xu, J., & Sablatnig, R. (2024). ECSIC: Epipolar Cross Attention for Stereo Image Compression. In 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) (pp. 3424–3433). https://doi.org/10.1109/WACV57701.2024.00340
2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
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ISBN:
9798350318920
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Date (published):
2024
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Event name:
2024 IEEE/CVF Winter Conference on Applications of Computer Vision - WACV 2024
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Event date:
3-Jan-2024 - 8-Jan-2024
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Event place:
Waikoloa, United States of America (the)
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Number of Pages:
10
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Peer reviewed:
Yes
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Keywords:
3D computer vision; Algorithms; formulations; Machine learning architectures
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Abstract:
In this paper, we present ECSIC, a novel learned method for stereo image compression. Our proposed method compresses the left and right images in a joint manner by exploiting the mutual information between the images of the stereo image pair using a novel stereo cross attention (SCA) module and two stereo context modules. The SCA module performs cross-attention restricted to the corresponding epipolar lines of the two images and processes them in parallel. The stereo context modules improve the entropy estimation of the second encoded image by using the first image as a context. We conduct an extensive ablation study demonstrating the effectiveness of the proposed modules and a comprehensive quantitative and qualitative comparison with existing methods. ECSIC achieves state-of-the-art performance in stereo image compression on the two popular stereo image datasets Cityscapes and InStereo2k while allowing for fast encoding and decoding.
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Project title:
KI-basierte Videokomprimierung für neue Technologien: GA 965502 (European Commission)
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Research Areas:
Visual Computing and Human-Centered Technology: 100%