Papers with Code 아카이브
2D Object Detection
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 15
- 평가표
- 20
- 보존된 평가 기록
- 57
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/ibaiGorordo/ONNX-YOLOv10-Object-Detection
https://github.com/ibaiGorordo/ONNX-YOLOv7-Object-Detection
YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
https://github.com/ibaiGorordo/ONNX-YOLOv9-MIT-Object-Detection
YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information
https://github.com/iberganzo/darknet
https://github.com/ibm/max-human-pose-estimator
Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
https://github.com/ibrahiemhss/android-yolo
https://github.com/ibrahimethemhamamci/dentex
Diffusion-Based Hierarchical Multi-Label Object Detection to Analyze Panoramic Dental X-rays
https://github.com/ice-melt/csdn-w9
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
https://github.com/icyeyeball/Peitent
https://github.com/idea-research/dab-detr
https://github.com/idea-research/dino
DN-DETR: Accelerate DETR Training by Introducing Query DeNoising
https://github.com/idea-research/grounded-sam-2
Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection
https://github.com/idea-research/stable-dino
A Strong and Reproducible Object Detector with Only Public Datasets
https://github.com/idea-research/stabledino
A Strong and Reproducible Object Detector with Only Public Datasets
https://github.com/idealo/imagededup
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
https://github.com/iduta/pyconvsegnet
Pyramidal Convolution: Rethinking Convolutional Neural Networks for Visual Recognition
https://github.com/iejMac/ScriptWriter
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/ifrit98/bengaliai
https://github.com/iibrahimli/unet_sem_seg
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/ikh-innovation/roboweldar-votenet
https://github.com/ikigai-aa/Automatic-License-Plate-Recognition
A Robust Real-Time Automatic License Plate Recognition Based on the YOLO Detector
https://github.com/ikigai-aa/Face-Mask-Detector-using-MobileNetV2
https://github.com/ikuokuo/start-scaled-yolov4
https://github.com/ikuto056/Estimating_Distance
ESPNetv2: A Light-weight, Power Efficient, and General Purpose Convolutional Neural Network
https://github.com/ildoonet/pytorch-randaugment
RandAugment: Practical automated data augmentation with a reduced search space
https://github.com/imagesegmentation2020/indoor
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/imagine5am/ARU-Net
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/imistyrain/ssd
https://github.com/imistyrain/ssd-windows
https://github.com/imkoushik22/Walmart-Hackathon
https://github.com/impiga/plain-detr
https://github.com/implus/CarDetectionExample
https://github.com/imrahulr/adversarial_robustness_pytorch
Towards Deep Learning Models Resistant to Adversarial Attacks
https://github.com/imshamsher/darknet
https://github.com/inacmor/mobiledets-yolov4-pytorch
MobileDets: Searching for Object Detection Architectures for Mobile Accelerators
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.