Update README.md

README.md

@@ -8,9 +8,10 @@ This is the official implementation of the paper "[DINO: DETR with Improved DeNo
 Authors: [Hao Zhang](https://scholar.google.com/citations?user=B8hPxMQAAAAJ&hl=zh-CN)\*, [Feng Li](https://fengli-ust.github.io/)\*, [Shilong Liu](https://www.lsl.zone/)\*, [Lei Zhang](https://www.leizhang.org/), [Hang Su](https://www.suhangss.me/), [Jun Zhu](https://ml.cs.tsinghua.edu.cn/~jun/index.shtml), [Lionel M. Ni](https://www.cse.ust.hk/~ni/), [Heung-Yeung Shum](https://scholar.google.com.hk/citations?user=9akH-n8AAAAJ&hl=en)
 
 # News
-[2022/3/13]: We release a strong open-set object detection model [Grounding DINO](https://arxiv.org/abs/2303.05499) that achieves the best results on open-set object detection tasks. It achieves **52.5** **zero-shot** AP on COCO detection, **without any COCO training data!** It achieves **63.0** AP on COCO after fine-tuning. Code and checkpoints will be available [here](https://github.com/IDEA-Research/GroundingDINO).
+[2023/4/22]: With better hyper-params, our DINO-4scale model achieves `49.7AP` under 12ep settings, please check [detrex: DINO](https://github.com/IDEA-Research/detrex/tree/main/projects/dino) for more details.
+[2023/3/13]: We release a strong open-set object detection model [Grounding DINO](https://arxiv.org/abs/2303.05499) that achieves the best results on open-set object detection tasks. It achieves **52.5** **zero-shot** AP on COCO detection, **without any COCO training data!** It achieves **63.0** AP on COCO after fine-tuning. Code and checkpoints will be available [here](https://github.com/IDEA-Research/GroundingDINO).
 </br>
-[2022/1/23]: DINO has been accepted to ICLR 2023!</br>
+[2023/1/23]: DINO has been accepted to ICLR 2023!</br>
 [2022/12/02]: Code for [Mask DINO](https://github.com/IDEA-Research/MaskDINO) is released (also in [detrex](https://github.com/IDEA-Research/detrex/tree/main/projects/maskdino))! Mask DINO further Achieves **51.7** and **59.0** box AP on COCO with a ResNet-50 and SwinL without extra detection data, **outperforming DINO** under the same setting!. </br>
 [2022/9/22]: We release a toolbox <font size=4>[**detrex**](https://github.com/IDEA-Research/detrex)</font> that provides state-of-the-art Transformer-based detection algorithms. It includes DINO **with better performance**. Welcome to use it! </br>
   - Supports Now: [DETR](https://arxiv.org/abs/2005.12872), [Deformble DETR](https://arxiv.org/abs/2010.04159), [Conditional DETR](https://arxiv.org/abs/2108.06152), [DAB-DETR](https://arxiv.org/abs/2201.12329), [DN-DETR](https://arxiv.org/abs/2203.01305), [DINO](https://arxiv.org/abs/2203.03605).