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New Transformer Model Enhances Pedestrian Crossing Prediction for Autonomous Driving

By PulseAugur Editorial · [2 sources] ·

Researchers have developed ADAPT (Adaptive Domain-Aware Pedestrian Crossing Transformer), a new multimodal framework designed to improve the prediction of pedestrian crossing intentions for autonomous driving. This system integrates visual data from RGB images, depth maps, and semantic maps with kinematic information such as pedestrian pose and ego-vehicle speed. ADAPT utilizes specialized modules including Swin Transformer V2 and Mamba for feature extraction and temporal modeling, with a sparse cross-modal attention mechanism to efficiently fuse complementary information. Experiments on benchmark datasets show ADAPT surpasses existing methods in accuracy and AUC while operating at a real-time inference speed. AI

IMPACT This research could lead to safer autonomous driving systems by improving the accuracy and speed of pedestrian intention prediction.

RANK_REASON The cluster contains a research paper detailing a new model and its performance on benchmark datasets.

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New Transformer Model Enhances Pedestrian Crossing Prediction for Autonomous Driving

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COVERAGE [2]

  1. arXiv cs.CV TIER_1 English(EN) · Md Mahfuzur Rahman, Pengzhan Zhou, A F M Abdun Noor, Md Imam Ahasan, Kah Ong Michael Goh, S. M. Hasan Mahmud, Md Mustafizur Rahman, Kaixin Gao ·

    Adaptive Cross-Modal Fusion with Sparse Attention for Pedestrian Crossing Intention Prediction

    arXiv:2607.12293v1 Announce Type: new Abstract: Predicting pedestrian crossing intention is a safety-critical task for autonomous driving, yet existing approaches often rely on single-modal inputs or dense multimodal fusion strategies that inadequately capture complementary visua…

  2. arXiv cs.CV TIER_1 English(EN) · Kaixin Gao ·

    Adaptive Cross-Modal Fusion with Sparse Attention for Pedestrian Crossing Intention Prediction

    Predicting pedestrian crossing intention is a safety-critical task for autonomous driving, yet existing approaches often rely on single-modal inputs or dense multimodal fusion strategies that inadequately capture complementary visual and kinematic information while introducing re…

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