https://github.com/brown-palm/ObjectPrompt
Learning Transferable Visual Models From Natural Language Supervision
Papers with Code 아카이브
2D Object Detection
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 평가표
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- 보존된 평가 기록
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/brunasil98/u-net_Cancer
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/bruthyu/bpt-vlm
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/brycexu/MR-Residual-Net
https://github.com/brytsknguyen/M-LOAM
MLOD: Awareness of Extrinsic Perturbation in Multi-LiDAR 3D Object Detection for Autonomous Driving
https://github.com/bt77/pointnet
VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection
https://github.com/buaaYYC/faster-rcnn-tensorflow
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/buaazyz/battery_detect
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/bubbliiiing/yolov4-pytorch
https://github.com/buiquangmanhhp1999/age_gender_estimation
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/bupt-ai-cz/LLVIP
https://github.com/bupt-ai-cz/hhcl-reid
Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net
https://github.com/buptdbj/darknet-windows-linux
https://github.com/burakalperen/Pytorch-Semantic-Segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/busyboxs/Some-resources-useful-for-me
Training Region-based Object Detectors with Online Hard Example Mining
https://github.com/busyboxs/What-I-have-star
https://github.com/busyboxs/faster_rcnn_voc
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/buyeah1109/KEN
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/buyeah1109/finc
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/bwconrad/masked-autoencoder
https://github.com/byahn2/clevr_ref
CLEVR-Ref+: Diagnosing Visual Reasoning with Referring Expressions
https://github.com/bytedance/next-vit
https://github.com/c1ph3rr/Deep-Residual-Learning-for-Image-Recognition
https://github.com/c1ph3rr/U-Net-Convolutional-Networks-For-Biomedicalimage-Segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/cabeen/neu-net
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/cai199626/PDNet
PDNet: Prior-model Guided Depth-enhanced Network for Salient Object Detection
https://github.com/caihaocong/Yolov3_AlexeyAB_Version
https://github.com/caihuaiguang/CHG-Shapley-for-Data-Selection
https://github.com/calmisential/TensorFlow2.0_ResNet
https://github.com/calmisential/YOLOv3_TensorFlow2
https://github.com/camenduru/grounded-segment-anything-colab
Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection
https://github.com/cameronchoi/r3det-copy
https://github.com/cameronthurston/CSAILVisionUpdated
Acquisition of Localization Confidence for Accurate Object Detection
https://github.com/camma-public/ssg-qa
EndoNet: A Deep Architecture for Recognition Tasks on Laparoscopic Videos
https://github.com/camma-public/ssg-vqa
EndoNet: A Deep Architecture for Recognition Tasks on Laparoscopic Videos
https://github.com/camma-public/tf-cholec80
EndoNet: A Deep Architecture for Recognition Tasks on Laparoscopic Videos
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.