mlsanityData to 14 Oct 2026

Lane detection with Position Embedding

arXiv 2203.12301 ↗First posted 23 Mar 2022cs.CVcited by 0

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Abstract (arXiv)

Recently, lane detection has made great progress in autonomous driving. RESA (REcurrent Feature-Shift Aggregator) is based on image segmentation. It presents a novel module to enrich lane feature after preliminary feature extraction with an ordinary CNN. For Tusimple dataset, there is not too complicated scene and lane has more prominent spatial features. On the basis of RESA, we introduce the method of position embedding to enhance the spatial features. The experimental results show that this method has achieved the best accuracy 96.93% on Tusimple dataset.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 22 of its 27 references that are in the map. First posted on arXiv 23 Mar 2022.

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22 of 27 references.

References · 22

  1. 2017Attention Is All You Needcited by 60,361
  2. 2018Self-Attention with Relative Position Representationscited by 1,120
  3. 2019Stand-Alone Self-Attention in Vision Modelscited by 542
  4. 2021Bottleneck Transformers for Visual Recognitioncited by 364
  5. 2019Attention Augmented Convolutional Networkscited by 363
  6. 2020Exploring Self-attention for Image Recognitioncited by 313
  7. 2017Spatial As Deep: Spatial CNN for Traffic Scene Understandingcited by 187
  8. 2020How Much Position Information Do Convolutional Neural Networks Encode?cited by 172
  9. 2020Keep your Eyes on the Lane: Real-time Attention-guided Lane Detectioncited by 138
  10. 2020Ultra Fast Structure-aware Deep Lane Detectioncited by 122
  11. 2020End-to-end Lane Shape Prediction with Transformerscited by 111
  12. 2020PolyLaneNet: Lane Estimation via Deep Polynomial Regressioncited by 95
10 more
  1. 2021CondLaneNet: a Top-to-down Lane Detection Framework Based on Conditional Convolutioncited by 95
  2. 2020Key Points Estimation and Point Instance Segmentation Approach for Lane Detectioncited by 77
  3. 2020RESA: Recurrent Feature-Shift Aggregator for Lane Detectioncited by 77
  4. 2021Focus on Local: Detecting Lane Marker from Bottom Up via Key Pointcited by 65
  5. 2019On Recognizing Texts of Arbitrary Shapes with 2D Self-Attentioncited by 59
  6. 2020End-to-End Lane Marker Detection via Row-wise Classificationcited by 47
  7. 2021LaneAF: Robust Multi-Lane Detection with Affinity Fieldscited by 41
  8. 2018LaneNet: Real-Time Lane Detection Networks for Autonomous Drivingcited by 39
  9. 2021Position, Padding and Predictions: A Deeper Look at Position Information in CNNscited by 26
  10. 2020How Can CNNs Use Image Position for Segmentation?cited by 8

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