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README.md

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-# Salience-DETR
-[CVPR 2024] Official implementation of Salience-DETR
+**Salience-DETR**: Enhancing Detection Transformer with Hierarchical Salience Filtering Refinement  
+===
+
+By [Xiuquan Hou](https://github.com/xiuqhou), [Meiqin Liu](https://scholar.google.com/citations?user=T07OWMkAAAAJ&hl=zh-CN&oi=ao), Senlin Zhang, [Ping Wei](https://scholar.google.com/citations?user=1OQBtdcAAAAJ&hl=zh-CN&oi=ao), [Badong Chen](https://scholar.google.com/citations?user=mq6tPX4AAAAJ&hl=zh-CN&oi=ao).
+
+<div align="center">
+    <img src="https://img.shields.io/github/license/xiuqhou/Salience-DETR.svg?color=blue" alt="license-Apache2.0">
+    <img src="https://img.shields.io/github/stars/xiuqhou/Salience-DETR" alt="Github-stars">
+</div>
+
+This repository is an official implementation of the Salience-DETR accepeted to **CVPR 2024** (score **553**).
+
+## ✨Highlights: 
+
+<div align="center">
+    <img src="images/Salience-DETR.svg">
+</div>
+
+1. We offer a deepened analysis for [scale bias and query redundancy](#id_1) issues of two-stage DETR-like methods.
+2. We present a query filtering mechanism to reduce the computational complexity by selectively encoding the most informative queries in each encoder layer and each feature level.
+3. The proposed salience supervision benefits to capture [fine-grained object contours](#id_2) even with bounding box annotations.
+4. Salience-DETR achieves **+4.0%**, **+0.2%**, and **+4.4%** AP on three challenging defect detection tasks, and comparable performance with about only **70\%** FLOPs on COCO 2017.
+5. Our model achieves **49.2** AP with a ResNet-50 backbone under 1x training.
+
+## 🔎Visualization:
+
+- Queries in the two-stage selection of existing DETR-like methods is usually **redundant** and have **scale bias** (left).
+- **Salience supervision** benefits to capture **object contours** even with only bounding box annotations, for both defect detection and object detection tasks (right).
+
+<h3 align="center">
+    <a><img src="images/query_visualization.svg" width="335" id="id_1"></a>
+    <a><img src="images/salience_visualization.svg" width="462" id="id_2"></a>
+</h3>
+
+## Reference
+
+If you find our work helpful for your research, please consider citing the following BibTeX entry.
+
+```bibtex
+@inproceedings{hou2024salience,
+  title={Salience-DETR: Enhancing Detection Transformer with Hierarchical Salience Filtering Refinement},
+  author={Hou, Xiuquan and Liu, Meiqin and Zhang, Senlin and Wei, Ping and Chen, Badong}
+  booktitle={CVPR},
+  year={2024}
+}
+```