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    Chapter and Conference Paper

    EdgeNeXt: Efficiently Amalgamated CNN-Transformer Architecture for Mobile Vision Applications

    In the pursuit of achieving ever-increasing accuracy, large and complex neural networks are usually developed. Such models demand high computational resources and therefore cannot be deployed on edge devices. ...

    Muhammad Maaz, Abdelrahman Shaker in Computer Vision – ECCV 2022 Workshops (2023)

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    Chapter and Conference Paper

    PS-ARM: An End-to-End Attention-Aware Relation Mixer Network for Person Search

    Person search is a challenging problem with various real-world applications, that aims at joint person detection and re-identification of a query person from uncropped gallery images. Although, previous study ...

    Mustansar Fiaz, Hisham Cholakkal, Sanath Narayan in Computer Vision – ACCV 2022 (2023)

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    Chapter and Conference Paper

    Video Instance Segmentation via Multi-Scale Spatio-Temporal Split Attention Transformer

    State-of-the-art transformer-based video instance segmentation (VIS) approaches typically utilize either single-scale spatio-temporal features or per-frame multi-scale features during the attention computation...

    Omkar Thawakar, Sanath Narayan, Jiale Cao, Hisham Cholakkal in Computer Vision – ECCV 2022 (2022)