Papers › OMR: Occlusion-Aware Memory-Based Refinement for Video Lane Detection

OMR: Occlusion-Aware Memory-Based Refinement for Video Lane Detection

14 Aug 2024arXiv:2408.07486archive 2025-07-28

Dongkwon Jin, Chang-Su Kim

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.

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Video_Memory dongkwonjin/OMR/Modeling/OpenLane-V/OMR/code/libs/video_memory.py official repository ran Apache-2.0 (permissive) · 61f23a70edc69c49 · report
call_culane_eval_custom dongkwonjin/omr/Modeling/OpenLane-V/OMR/code/evaluation/evaluate_iou_official.py official repository ran Apache-2.0 (permissive) · 5b1117c2c47c0666 · report
discrete_cross_iou dongkwonjin/omr/Modeling/OpenLane-V/OMR/code/evaluation/evaluate_iou_laneatt.py official repository ran Apache-2.0 (permissive) · 756bc2a2cd32caeb · report
draw_lane dongkwonjin/omr/Modeling/OpenLane-V/OMR/code/evaluation/evaluate_iou_laneatt.py official repository ran Apache-2.0 (permissive) · b274c90d2c686b65 · report
read_helper dongkwonjin/omr/Modeling/OpenLane-V/OMR/code/evaluation/evaluate_iou_official.py official repository ran Apache-2.0 (permissive) · a82bfd9d8b8b5cee · report
call_culane_eval_custom_sampling dongkwonjin/omr/Modeling/OpenLane-V/OMR/code/evaluation/evaluate_iou_official.py official repository unverified Apache-2.0 (permissive) · e45a4247d7919703 · report

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Data AugmentationLane Detection

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