https://github.com/yeezhu/SPN.pytorch
Soft Proposal Networks for Weakly Supervised Object Localization
Papers with Code 아카이브
Object
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Replace the cat with a British Shorthair cat of the breed with bulging yellow eyes
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/yelantingfeng/pyLucid
https://github.com/yeliudev/catnet
iSAID: A Large-scale Dataset for Instance Segmentation in Aerial Images
https://github.com/yenchenlin/inerf-public
https://github.com/yeonsikch/Unbiased-Teacher
https://github.com/yeqiuyi/caffe-ssd
https://github.com/yfnn/fused-model
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/yfnn/person_subclass
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/yformer/EfficientSAM
https://github.com/yhbcode000/MMDetection3D-Eloss
Exploring Data Augmentation for Multi-Modality 3D Object Detection
https://github.com/yhenon/pytorch-retinanet
https://github.com/yifan-you-37/omnihang
https://github.com/yijiaceline/Final-Project-Group4
https://github.com/yimingcuicuicui/faq
FAQ: Feature Aggregated Queries for Transformer-based Video Object Detectors
https://github.com/yiningzeng/darknet-fork-from-AlexeyAB
https://github.com/yiranvang/TransCenter_official
TransCenter: Transformers with Dense Representations for Multiple-Object Tracking
https://github.com/yizhe-ang/detectron2-1
Adversarial Examples for Semantic Segmentation and Object Detection
https://github.com/yj-littlesky/py-faster-rcnn
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/ykasten/layered-neural-atlases
https://github.com/yktangac/CenterHarDNet
https://github.com/ykzzyk/vision6d
Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimation
https://github.com/ylabbe/cosypose
CosyPose: Consistent multi-view multi-object 6D pose estimation
https://github.com/ylxiao88/CenterNet
https://github.com/yongheng1991/3D-point-capsule-networks
https://github.com/yoojy31/mixture-density-object-detector
Training Multi-Object Detector by Estimating Bounding Box Distribution for Input Image
https://github.com/yorkeyao/automated-retail-checkout
Attribute Descent: Simulating Object-Centric Datasets on the Content Level and Beyond
https://github.com/yoshitomo-matsubara/torchdistill
Split Computing for Complex Object Detectors: Challenges and Preliminary Results
https://github.com/you-leee/deep-nn-examples
https://github.com/youchangxin/YOLOv4_tensorflow2
https://github.com/yousefis/darknet-ocr
https://github.com/youssef-kishk/ROS-Based-Robot-Object-Detection-Recognition
https://github.com/youtang1993/mixture-model-based-object-detector
Training Multi-Object Detector by Estimating Bounding Box Distribution for Input Image
https://github.com/yqyao/FCOS_PLUS
https://github.com/yqyao/cross_focal_loss
Cross-dataset Training for Class Increasing Object Detection
https://github.com/yqyao/ssd.pytorch
https://github.com/yshah43/DPOD
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.