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   Articles with "masked image" as a keyword



An Experimental Study on Exploring Strong Lightweight Vision Transformers via Masked Image Modeling Pre-training

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recommendations! Published in 2024 at "International Journal of Computer Vision"

DOI: 10.1007/s11263-024-02327-w

Abstract: Masked image modeling (MIM) pre-training for large-scale vision transformers (ViTs) has enabled promising downstream performance on top of the learned self-supervised ViT features. In this paper, we question if the extremely simple lightweight ViTs’ fine-tuning… read more here.

Keywords: image modeling; vision; masked image; usepackage ... See more keywords

Simplifying Masked Image Modeling With Symmetric Masking and Contrastive Learning

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recommendations! Published in 2025 at "IEEE Access"

DOI: 10.1109/access.2025.3589488

Abstract: Masked image modeling (MIM) has emerged as an effective self-supervised learning paradigm for pre-training Vision Transformers (ViTs) by reconstructing missing pixels from masked image regions. While prior approaches have demonstrated strong performance, they typically rely… read more here.

Keywords: simplifying masked; image modeling; image; masked image ... See more keywords

Dynamics of Masked Image Modeling in Hyperspectral Image Classification

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recommendations! Published in 2025 at "IEEE Transactions on Geoscience and Remote Sensing"

DOI: 10.1109/tgrs.2025.3558432

Abstract: Masked image modeling (MIM), a common self-supervised learning (SSL) technique, has been extensively studied for remote sensing (RS) image processing. Nevertheless, its effectiveness for hyperspectral imagery (HSI) remains underexplored due to the distinct data structures… read more here.

Keywords: classification; image modeling; image; hsi ... See more keywords

MOODv2: Masked Image Modeling for Out-of-Distribution Detection

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recommendations! Published in 2024 at "IEEE Transactions on Pattern Analysis and Machine Intelligence"

DOI: 10.1109/tpami.2024.3412004

Abstract: The crux of effective out-of-distribution (OOD) detection lies in acquiring a robust in-distribution (ID) representation, distinct from OOD samples. While previous methods predominantly leaned on recognition-based techniques for this purpose, they often resulted in shortcut… read more here.

Keywords: detection; score functions; image modeling; distribution ... See more keywords