From c9e35448fe91f51d81ada6a430e9c8cfc932daab Mon Sep 17 00:00:00 2001 From: Jinghao Zhou Date: Mon, 13 Dec 2021 14:52:38 +0800 Subject: [PATCH] add models with random masking --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 8f7e03e..a4d1c60 100644 --- a/README.md +++ b/README.md @@ -15,7 +15,7 @@ iBOT is a novel self-supervised pre-training framework that performs masked imag ## Update :tada: -- Update - ViT-B/16 with random masking and a relatively larger prediction ratio [0.65, 0.75] perform slighly better than block-wise masking with the ratio [0.1, 0.5]. For example, this model can achieve an **84.0%** accuracy in ImageNet-1K fine-tuning and a **51.4 box AP** in COCO object detection. +- Update - ViT-B/16 with random masking and a relatively larger prediction ratio [0.65, 0.75] perform slighly better than block-wise masking with the ratio [0.1, 0.5]. For example, this model can achieve an **84.0%** accuracy in ImageNet-1K fine-tuning and a **51.5 box AP** in COCO object detection. - December 2021 - Release the code and pre-trained [models](https://github.com/bytedance/ibot#pre-trained-models). - November 2021 - Release the pre-print on [arXiv](https://arxiv.org/abs/2111.07832).