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태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/res2net_deeplabv3
Rethinking Atrous Convolution for Semantic Image Segmentation
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/res2net_faster_rcnn
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/res2net_yolov3
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/resnet50_adv_pruning
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/resnetv2_50_frn
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/retinanet_resnet101
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/retinanet_resnet152
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/rfcn
R-FCN: Object Detection via Region-based Fully Convolutional Networks
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/STGAN
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/TokenFusion
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/UNet3%2B
UNet++: A Nested U-Net Architecture for Medical Image Segmentation
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/ViG
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/ssd_mobilenetV2
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/ssd_mobilenetV2_FPNlite
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/ssd_resnet34
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/ssd_resnet_34
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/tinydarknet
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/u2net
U$^2$-Net: Going Deeper with Nested U-Structure for Salient Object Detection
https://github.com/2023-MindSpore-1/ms-code-22
https://github.com/2023-MindSpore-1/ms-code-220/tree/main/SRC
SRCN3D: Sparse R-CNN 3D for Compact Convolutional Multi-View 3D Object Detection and Tracking
https://github.com/2023-MindSpore-1/ms-code-220/tree/main/textrcnn
PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection
https://github.com/2023-MindSpore-1/ms-code-222/tree/main/SRFlow
SRFlow: Learning the Super-Resolution Space with Normalizing Flow
https://github.com/2023-MindSpore-1/ms-code-222/tree/main/pointRCNN
PointRCNN: 3D Object Proposal Generation and Detection from Point Cloud
https://github.com/2023-MindSpore-1/ms-code-223/tree/main/RetinaNet
https://github.com/2023-MindSpore-1/ms-code-223/tree/main/ShuffleNet
ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
https://github.com/2023-MindSpore-1/ms-code-31
https://github.com/2023-MindSpore-1/ms-code-32
https://github.com/2023-MindSpore-1/ms-code-34
https://github.com/2023-MindSpore-1/ms-code-37
https://github.com/2023-MindSpore-1/ms-code-38
ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
https://github.com/2023-MindSpore-1/ms-code-39
https://github.com/2023-MindSpore-1/ms-code-40
ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design
https://github.com/2023-MindSpore-1/ms-code-41
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
https://github.com/2023-MindSpore-1/ms-code-44
https://github.com/2023-MindSpore-1/ms-code-46
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.