Papers with Code 아카이브
Object Detection
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 39
- 평가표
- 124
- 보존된 평가 기록
- 977
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/rahulvigneswaran/longtail-buzz
VirTex: Learning Visual Representations from Textual Annotations
https://github.com/rahzaazhar/Test-Remote
https://github.com/rainofmine/Face_Attention_Network
https://github.com/raisinglc/object_detection_SSD
https://github.com/raja-kumar/folding-batchnorm
Data-Free Quantization Through Weight Equalization and Bias Correction
https://github.com/rajatashhpa/1
https://github.com/rajathik/ObjectDetection
https://github.com/rajatkoner08/oodformer
https://github.com/rajatmodi62/occludedactionbenchmark
MViTv2: Improved Multiscale Vision Transformers for Classification and Detection
https://github.com/rajatsaini0294/lambda-mobilenets
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
https://github.com/rajkumargithub/densenet.mura
Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition
https://github.com/rajneeshaggarwal/google-efficientnet
https://github.com/rajs25/Object-Detection
https://github.com/ramanakshay/clip
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/rami0205/ngramswin
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
https://github.com/raphael-cohen/capsnet_for_Faster-RCNN
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/rasd3/3d-cvf
https://github.com/raspstephan/sugar-flower-fish-or-gravel
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/rauleun/point-transformer-tf2
https://github.com/raun1/Complementary_Segmentation_Network
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/raun1/Complementary_Segmentation_Network-Raw-Code-Available-Under-Construction-
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/raun1/MICCAI2018---Complementary_Segmentation_Network-Raw-Code
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/raun1/MICCAI2018---Complementary_Segmentation_Network-Raw-Code-Available-Under-Construction-
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/raunak-sood2003/Automated-Lung-Segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/raven-dehaze-work/DeblurGanToDehaze
DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks
https://github.com/ravenagcaoili/yolov3
https://github.com/ravenwritingdesk/py-faster-rcnn-master
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/ravi02512/efficientdet-keras
https://github.com/ravi0531rp/DeepDrive
https://github.com/ravikothari510/crossattention_radar_detector
RAMP-CNN: A Novel Neural Network for Enhanced Automotive Radar Object Recognition
https://github.com/ravindra579/object-detection_yolov4
https://github.com/ravindu-yasas-nagasinghe/kepp
Multiclass Confidence and Localization Calibration for Object Detection
https://github.com/raycad/object-detection
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/raymon-tian/hourglass-facekeypoints-detection
Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
https://github.com/razvancaramalau/Sequential-GCN-for-Active-Learning
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.