OMR: Occlusion-Aware Memory-Based Refinement for Video Lane Detection
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arXiv
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| Auteurs principaux: | , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866911988277313536 |
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| author | Jin, Dongkwon Kim, Chang-Su |
| author_facet | Jin, Dongkwon Kim, Chang-Su |
| contents | A novel algorithm for video lane detection is proposed in this paper. First, we extract a feature map for a current frame and detect a latent mask for obstacles occluding lanes. Then, we enhance the feature map by developing an occlusion-aware memory-based refinement (OMR) module. It takes the obstacle mask and feature map from the current frame, previous output, and memory information as input, and processes them recursively in a video. Moreover, we apply a novel data augmentation scheme for training the OMR module effectively. Experimental results show that the proposed algorithm outperforms existing techniques on video lane datasets. Our codes are available at https://github.com/dongkwonjin/OMR. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_07486 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | OMR: Occlusion-Aware Memory-Based Refinement for Video Lane Detection Jin, Dongkwon Kim, Chang-Su Computer Vision and Pattern Recognition A novel algorithm for video lane detection is proposed in this paper. First, we extract a feature map for a current frame and detect a latent mask for obstacles occluding lanes. Then, we enhance the feature map by developing an occlusion-aware memory-based refinement (OMR) module. It takes the obstacle mask and feature map from the current frame, previous output, and memory information as input, and processes them recursively in a video. Moreover, we apply a novel data augmentation scheme for training the OMR module effectively. Experimental results show that the proposed algorithm outperforms existing techniques on video lane datasets. Our codes are available at https://github.com/dongkwonjin/OMR. |
| title | OMR: Occlusion-Aware Memory-Based Refinement for Video Lane Detection |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2408.07486 |