doctorkey/lshfm.detection

Object detection of Distilling Knowledge by Mimicking Features.

Hi there 👋. Welcome to Guo-Hua Wang's profile!

Guo-Hua Wang is currently a researcher and developer for deep learning. He focuses on:

• Multi-model Learning:
  • Knowledge Distillation: LSHFM.singleclassification, LSHFM.multiclassification, LSHFM.detection
  • Model Compression/Acceleration: Practise
• Few-label Learning:
  • Semi-Supervised Learning: R2D2.pytorch
  • Few-shot Learning: Practise
• Image Related Tasks:
  • Image Classification: LSHFM.singleclassification, LSHFM.multiclassification
  • Object Detection: LSHFM.detection
  • Semantic Segmentation: C-3PO
  • Change Detection: C-3PO
  • Image Retrieval: DIGIX_2020_B_image_retrieval, CBIR, image_retrieval_demo
  • Image Compression: DCVC

💼 Projects

📅 Dates	🎁 Projects	⭐ Stars	📚 Forks	🛎 Issues	📬 Pull requests
2022.11-2023.3	Practise
2023.1-2023.3	njuthesis
2022.3-2022.10	DCVC
2021.7-2021.11	C-3PO
2020.8-2020.11	DIGIX_2020_B_image_retrieval
2020.1-2020.8	LSHFM.singleclassification
2020.1-2020.8	LSHFM.multiclassification
2020.1-2020.8	LSHFM.detection
2019.1-2019.12	R2D2.pytorch

📊 Github stats

lshfm.detection's Issues

A question about COCO results in your paper

hi, thanks for your sharing ~
In your paper table 15, the result of resnet50 on COCO dataset mAP is up to 77.16,I was wondering how you calculated? Is it the official calculation method?
so far, SOTA of COCO detection is 63.3mAP, How did you to improve to such a high level of precision?