update README

SangbumChoi · Jan 16, 2023 · 2e6bc63 · 2e6bc63
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diff --git a/README.md b/README.md
@@ -27,6 +27,11 @@ Implementation of paper:
 ## What's New
 
 - [2023.01.06] Release P6 models and enhance the performance of P5 models. ⭐️ [Benchmark](#Benchmark)
+    - Renew the neck of the detector with a BiC module and SimCSPSPPF Block.
+    - Propose an anchor-aided training (AAT) strategy.
+    - Involve a new self-distillation strategy for small models of YOLOv6.
+    - Expand YOLOv6 and hit a new
+SOTA performance on the COCO dataset.
 - [2022.11.04] Release [base models](configs/base/README.md) to simplify the training and deployment process.
 - [2022.09.06] Customized quantization methods. 🚀 [Quantization Tutorial](./tools/qat/README.md)
 - [2022.09.05] Release M/L models and update N/T/S models with enhanced performance. 

diff --git a/README_cn.md b/README_cn.md
@@ -17,6 +17,10 @@
 
 ## 更新日志
 - [2023.01.06] 发布大分辨率 P6 模型以及对 P5 模型做了全面的升级 ⭐️ [模型指标](#模型指标)
+    - 添加 BiC 模块 和 SimCSPSPPF 模块以增强检测网络颈部的表征能力。
+    - 提出一个锚点辅助训练 (AAT) 策略。
+    - 为 YOLOv6 小模型引入一个新的自蒸馏训练策略。
+    - 扩展 YOLOv6 并在 COCO 上取得了实时目标检测 SOTA 的精度和速度。
 - [2022.11.04] 发布 [基础版模型](configs/base/README_cn.md) 简化训练部署流程
 - [2022.09.06] 定制化的模型量化加速方法 🚀 [量化教程](./tools/qat/README.md)
 - [2022.09.05] 发布 M/L 模型，并且进一步提高了 N/T/S 模型的性能