https://github.com/MindSpore-paper-code-2/code3/tree/main/u2net
U$^2$-Net: Going Deeper with Nested U-Structure for Salient Object Detection
Papers with Code 아카이브
2D Object Detection
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/MindSpore-paper-code-2/code3/tree/main/wave_mlp
https://github.com/MindSpore-paper-code-2/code3/tree/main/yolov3_tiny
https://github.com/MindSpore-paper-code-2/code399/tree/main/Transformer
A Simple Single-Scale Vision Transformer for Object Localization and Instance Segmentation
https://github.com/MindSpore-paper-code-2/code400/tree/main/Efficientnet
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/MindSpore-paper-code-2/code400/tree/main/MAE
Point-M2AE: Multi-scale Masked Autoencoders for Hierarchical Point Cloud Pre-training
https://github.com/MindSpore-paper-code-2/code400/tree/main/MobileNet/mobilenetv2
https://github.com/MindSpore-paper-code-2/code400/tree/main/MobileNet/mobilenetv3
MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer
https://github.com/MindSpore-paper-code-3/code1/tree/main/Auto-DeepLab
FNA++: Fast Network Adaptation via Parameter Remapping and Architecture Search
https://github.com/MindSpore-paper-code-3/code1/tree/main/augvit
How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers
https://github.com/MindSpore-paper-code-3/code10/tree/main/FCANet
https://github.com/MindSpore-paper-code-3/code10/tree/main/FCOS
https://github.com/MindSpore-paper-code-3/code10/tree/main/FSAF
Feature Selective Anchor-Free Module for Single-Shot Object Detection
https://github.com/MindSpore-paper-code-3/code10/tree/main/FreeAnchor
FreeAnchor: Learning to Match Anchors for Visual Object Detection
https://github.com/MindSpore-paper-code-3/code10/tree/main/Gold_YOLO
Gold-YOLO: Efficient Object Detector via Gather-and-Distribute Mechanism
https://github.com/MindSpore-paper-code-3/code10/tree/main/GridRCNN
An Implementation of Faster RCNN with Study for Region Sampling
https://github.com/MindSpore-paper-code-3/code10/tree/main/fairmot
FairMOT: On the Fairness of Detection and Re-Identification in Multiple Object Tracking
https://github.com/MindSpore-paper-code-3/code10/tree/main/faster_rcnn_dcn
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/MindSpore-paper-code-3/code10/tree/main/fastscnn
https://github.com/MindSpore-paper-code-3/code10/tree/main/foveabox
https://github.com/MindSpore-paper-code-3/code10/tree/main/frustum-pointnet
https://github.com/MindSpore-paper-code-3/code10/tree/main/hardnet
https://github.com/MindSpore-paper-code-3/code2/tree/main/Deepsort
https://github.com/MindSpore-paper-code-3/code2/tree/main/csd
https://github.com/MindSpore-paper-code-3/code2/tree/main/darknet53
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/MindSpore-paper-code-3/code3/tree/main/FCANet
https://github.com/MindSpore-paper-code-3/code3/tree/main/FCN8s
https://github.com/MindSpore-paper-code-3/code3/tree/main/FCOS
https://github.com/MindSpore-paper-code-3/code3/tree/main/FaceAttribute
https://github.com/MindSpore-paper-code-3/code3/tree/main/FaceDetection
Face Detection with End-to-End Integration of a ConvNet and a 3D Model
https://github.com/MindSpore-paper-code-3/code3/tree/main/FaceNet
https://github.com/MindSpore-paper-code-3/code3/tree/main/fairmot
FairMOT: On the Fairness of Detection and Re-Identification in Multiple Object Tracking
https://github.com/MindSpore-paper-code-3/code3/tree/main/faster_rcnn_dcn
https://github.com/MindSpore-paper-code-3/code3/tree/main/fastscnn
https://github.com/MindSpore-paper-code-3/code4/tree/main/HDR-Transformer
A Simple Single-Scale Vision Transformer for Object Localization and Instance Segmentation
https://github.com/MindSpore-paper-code-3/code4/tree/main/HireMLP
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.