Non-Hierarchical Transformers for Pedestrian Segmentation

2023-07-11 · Amani Kiruga, Xi Peng

We propose a methodology to address the challenge of instance segmentation in autonomous systems, specifically targeting accessibility and inclusivity. Our approach utilizes a non-hierarchical Vision Transformer variant, EVA-02, combined with a Cascade Mask R-CNN mask head. Through fine-tuning on the AVA instance segmentation challenge dataset, we achieved a promising mean Average Precision (mAP) of 52.68\% on the test set. Our results demonstrate the efficacy of ViT-based architectures in enhancing vision capabilities and accommodating the unique needs of individuals with disabilities.

📄 PDF Abstract BibTeX arXiv:2311.02506

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Instance Segmentation Segmentation Semantic Segmentation

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