Green Video Camouflaged Object Detection
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866908190575165440 |
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| author | Wang, Xinyu Chen, Hong-Shuo Zhou, Zhiruo You, Suya Madni, Azad M. Kuo, C. -C. Jay |
| author_facet | Wang, Xinyu Chen, Hong-Shuo Zhou, Zhiruo You, Suya Madni, Azad M. Kuo, C. -C. Jay |
| contents | Camouflaged object detection (COD) aims to distinguish hidden objects embedded in an environment highly similar to the object. Conventional video-based COD (VCOD) methods explicitly extract motion cues or employ complex deep learning networks to handle the temporal information, which is limited by high complexity and unstable performance. In this work, we propose a green VCOD method named GreenVCOD. Built upon a green ICOD method, GreenVCOD uses long- and short-term temporal neighborhoods (TN) to capture joint spatial/temporal context information for decision refinement. Experimental results show that GreenVCOD offers competitive performance compared to state-of-the-art VCOD benchmarks. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_10914 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Green Video Camouflaged Object Detection Wang, Xinyu Chen, Hong-Shuo Zhou, Zhiruo You, Suya Madni, Azad M. Kuo, C. -C. Jay Computer Vision and Pattern Recognition Camouflaged object detection (COD) aims to distinguish hidden objects embedded in an environment highly similar to the object. Conventional video-based COD (VCOD) methods explicitly extract motion cues or employ complex deep learning networks to handle the temporal information, which is limited by high complexity and unstable performance. In this work, we propose a green VCOD method named GreenVCOD. Built upon a green ICOD method, GreenVCOD uses long- and short-term temporal neighborhoods (TN) to capture joint spatial/temporal context information for decision refinement. Experimental results show that GreenVCOD offers competitive performance compared to state-of-the-art VCOD benchmarks. |
| title | Green Video Camouflaged Object Detection |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2501.10914 |