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11/03/2022
Could Giant Pretrained Image Models Extract Universal Representations?
Frozen pretrained models have become a viable alternative to the pretrai...
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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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12/29/2021
A Simple Baseline for Zero-shot Semantic Segmentation with Pre-trained Vision-language Model
Recently, zero-shot image classification by vision-language pre-training...
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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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11/04/2021
Bootstrap Your Object Detector via Mixed Training
We introduce MixTraining, a new training paradigm for object detection t...
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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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03/25/2021
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
This paper presents a new vision Transformer, called Swin Transformer, t...
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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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03/26/2020
