https://github.com/ogatarina-sq/secyolov7
YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
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/ohosseini/DOCS-caffe
https://github.com/ohosseini/DOCS-pytorch
https://github.com/oist/DenseObjectAnnotation
https://github.com/oist/DenseObjectDetection
https://github.com/okboseong/darknet
https://github.com/oki5656/Estimating_Distance
ESPNetv2: A Light-weight, Power Efficient, and General Purpose Convolutional Neural Network
https://github.com/olivesgatech/cure-or
CURE-OR: Challenging Unreal and Real Environments for Object Recognition
https://github.com/oljikeboost/PlayerTracking
FairMOT: On the Fairness of Detection and Re-Identification in Multiple Object Tracking
https://github.com/omkar13/MaskTrack
https://github.com/omni-us/squeezedet-keras
https://github.com/omniobject3d/omniobject3d
https://github.com/oorrppp2/darknet-pose
https://github.com/open-edge-platform/geti
https://github.com/open-edge-platform/training_extensions
https://github.com/open-mmlab/OpenUnReID
Self-paced Contrastive Learning with Hybrid Memory for Domain Adaptive Object Re-ID
https://github.com/open-mmlab/mmaction2
Rethinking Self-supervised Correspondence Learning: A Video Frame-level Similarity Perspective
https://github.com/open-mmlab/mmclassification
MViTv2: Improved Multiscale Vision Transformers for Classification and Detection
https://github.com/open-mmlab/mmpose
https://github.com/open-mmlab/mmrazor
https://github.com/open-mmlab/mmsegmentation
https://github.com/open-mmlab/mmselfsup
Dense Contrastive Learning for Self-Supervised Visual Pre-Training
https://github.com/open-mmlab/mmyolo
YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
https://github.com/opencv/openvino_training_extensions
https://github.com/openseg-group/OCNet.pytorch
https://github.com/openseg-group/openseg.pytorch
https://github.com/openvinotoolkit/anomalib
The MVTec 3D-AD Dataset for Unsupervised 3D Anomaly Detection and Localization
https://github.com/openvinotoolkit/training_extensions
https://github.com/optas/shapeglot
https://github.com/optimalscale/detgpt
https://github.com/orhir/EdgeCape
A Graph-Based Approach for Category-Agnostic Pose Estimation
https://github.com/orpatashnik/local-prompt-mixing
Localizing Object-level Shape Variations with Text-to-Image Diffusion Models
https://github.com/osmr/imgclsmob
ESPNetv2: A Light-weight, Power Efficient, and General Purpose Convolutional Neural Network
https://github.com/otaheri/GrabNet
https://github.com/otamajakusi/darknet-yolov4
https://github.com/otoofim/ObjLocalisation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.