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06/09/2022
On Data Scaling in Masked Image Modeling
An important goal of self-supervised learning is to enable model pre-tra...
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05/27/2022
Contrastive Learning Rivals Masked Image Modeling in Fine-tuning via Feature Distillation
Masked image modeling (MIM) learns representations with remarkably good ...
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05/26/2022
Revealing the Dark Secrets of Masked Image Modeling
Masked image modeling (MIM) as pre-training is shown to be effective for...
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04/22/2022
iCAR: Bridging Image Classification and Image-text Alignment for Visual Recognition
Image classification, which classifies images by pre-defined categories,...
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11/18/2021
SimMIM: A Simple Framework for Masked Image Modeling
This paper presents SimMIM, a simple framework for masked image modeling...
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11/18/2021
Swin Transformer V2: Scaling Up Capacity and Resolution
We present techniques for scaling Swin Transformer up to 3 billion param...
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05/10/2021
Self-Supervised Learning with Swin Transformers
We are witnessing a modeling shift from CNN to Transformers in computer ...
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11/19/2020
Propagate Yourself: Exploring Pixel-Level Consistency for Unsupervised Visual Representation Learning
Contrastive learning methods for unsupervised visual representation lear...
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06/25/2020
Parametric Instance Classification for Unsupervised Visual Feature Learning
This paper presents parametric instance classification (PIC) for unsuper...
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03/19/2020
Spatially Adaptive Inference with Stochastic Feature Sampling and Interpolation
In the feature maps of CNNs, there commonly exists considerable spatial ...
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04/25/2019