Kheem-Dh/End-End-Object-Detection-By-Using-Transformers-
This paper presents a method for object detection that addresses the problem of direct set prediction. It eliminates the need for multiple components and simplifies the process by avoiding the need for manual intervention.The main components of a framework known as DEtection TRansformer are the transformer and the matching mechanism. This paper shows that the relationship between the two components is strong enough to explain the relationship between the two datasets,The DETR framework achieves a fast R-CNN baseline and is capable of providing uniform panoptic segmentation. It is also well-designed to improve its performance.
No commits in the last 6 months.
Stars
2
Forks
—
Language
Jupyter Notebook
License
—
Category
Last pushed
Aug 24, 2022
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/computer-vision/Kheem-Dh/End-End-Object-Detection-By-Using-Transformers-"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
lucasjinreal/yolov7_d2
🔥🔥🔥🔥 (Earlier YOLOv7 not official one) YOLO with Transformers and Instance Segmentation, with...
fredzzhang/upt
[CVPR'22] Official PyTorch implementation for paper "Efficient Two-Stage Detection of...
coderonion/awesome-yolo-object-detection
🚀🚀🚀 A collection of some awesome public YOLO object detection series projects and the related...
qubvel/rt-pose
Real-time pose estimation pipeline with 🤗 Transformers
Atten4Vis/GroupDETR
[ICCV 2023] Group DETR: Fast DETR Training with Group-Wise One-to-Many Assignment