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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/pku-epic/dexgraspnet
DexGraspNet: A Large-Scale Robotic Dexterous Grasp Dataset for General Objects Based on Simulation
https://github.com/playerkk/face-py-faster-rcnn
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/pminhtam/xnor_conv_pytorch_extension
https://github.com/poel22/covproject
https://github.com/pohlinwei/AComPianist
Building Emotional Machines: Recognizing Image Emotions through Deep Neural Networks
https://github.com/poier/PreView
Learning Pose Specific Representations by Predicting Different Views
https://github.com/polospeter/TensorFlow-Advanced-Techniques-Specialization
https://github.com/poojabhore12/SocialDistancing-Detector
https://github.com/popcornell/keras-triplet-center-loss
https://github.com/potterhsu/easy-faster-rcnn.pytorch
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/ppengtang/pcl.pytorch
Multiple Instance Detection Network with Online Instance Classifier Refinement
https://github.com/ppokhare/Handling-Imbalanced-Dataset-for-classification-task
https://github.com/ppwwyyxx/FRN-on-common-ImageNet-baseline
https://github.com/pranavbajoria93/3D_Reconstruction_3DR2N2
3D-R2N2: A Unified Approach for Single and Multi-view 3D Object Reconstruction
https://github.com/pranavjadhav001/detr_keras
https://github.com/pranavmvp/Crowd-Density-Estimator-via-Object-Detection
https://github.com/prannaykaul/mm-ovod
Multi-Modal Classifiers for Open-Vocabulary Object Detection
https://github.com/pransen/faster_rcnn
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/pratikshaya/image-data-augmentation-for-object-detection
https://github.com/pravinthsam/Ilios-3D-model-generation
https://github.com/pren1/Group-Normalization-Example
https://github.com/preste-ai/camera_ai_whiteboard
https://github.com/preste-nakam/AI_whiteboard
https://github.com/pricha0912/objectRecognition
https://github.com/princewang1994/R-FCN.pytorch
R-FCN: Object Detection via Region-based Fully Convolutional Networks
https://github.com/princewang1994/RFCN_CoupleNet.pytorch
R-FCN: Object Detection via Region-based Fully Convolutional Networks
https://github.com/pritish-mahajan/Apricitas
https://github.com/purplearrow/pytorch-dense-correspondence
Dense Object Nets: Learning Dense Visual Object Descriptors By and For Robotic Manipulation
https://github.com/pvdhove/owl-mask-rcnn
https://github.com/pwc-1/Paper-9/tree/main/1/vitdet
Exploring Plain Vision Transformer Backbones for Object Detection
https://github.com/pwc-1/Paper-9/tree/main/3/ssFPN
ssFPN: Scale Sequence (S^2) Feature Based-Feature Pyramid Network for Object Detection
https://github.com/pytorch/captum
https://github.com/pytorch/vision
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/qdu1995/DQSD
https://github.com/qfgaohao/pytorch-ssd
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.