Papers with Code 아카이브
2D Object Detection
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 15
- 평가표
- 20
- 보존된 평가 기록
- 57
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/2023-MindSpore-1/ms-code-117
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/2023-MindSpore-1/ms-code-118
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/2023-MindSpore-1/ms-code-14
ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
https://github.com/2023-MindSpore-1/ms-code-142
MSG-Transformer: Exchanging Local Spatial Information by Manipulating Messenger Tokens
https://github.com/2023-MindSpore-1/ms-code-143
Sparse Instance Activation for Real-Time Instance Segmentation
https://github.com/2023-MindSpore-1/ms-code-147
CIR-Net: Cross-modality Interaction and Refinement for RGB-D Salient Object Detection
https://github.com/2023-MindSpore-1/ms-code-149
EdgeNeXt: Efficiently Amalgamated CNN-Transformer Architecture for Mobile Vision Applications
https://github.com/2023-MindSpore-1/ms-code-151
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/2023-MindSpore-1/ms-code-16/tree/main/Contents
https://github.com/2023-MindSpore-1/ms-code-16/tree/main/augvit
How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers
https://github.com/2023-MindSpore-1/ms-code-161
https://github.com/2023-MindSpore-1/ms-code-162
Deep High-Resolution Representation Learning for Visual Recognition
https://github.com/2023-MindSpore-1/ms-code-167
Rethinking Atrous Convolution for Semantic Image Segmentation
https://github.com/2023-MindSpore-1/ms-code-17/tree/main/CBAM
https://github.com/2023-MindSpore-1/ms-code-170
Rethinking Atrous Convolution for Semantic Image Segmentation
https://github.com/2023-MindSpore-1/ms-code-174
https://github.com/2023-MindSpore-1/ms-code-175
https://github.com/2023-MindSpore-1/ms-code-176
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
https://github.com/2023-MindSpore-1/ms-code-177
https://github.com/2023-MindSpore-1/ms-code-179
Bridged Transformer for Vision and Point Cloud 3D Object Detection
https://github.com/2023-MindSpore-1/ms-code-18/tree/main/ISyNet
ISyNet: Convolutional Neural Networks design for AI accelerator
https://github.com/2023-MindSpore-1/ms-code-18/tree/main/lite-hrnet
https://github.com/2023-MindSpore-1/ms-code-18/tree/main/lresnet100e_ir
https://github.com/2023-MindSpore-1/ms-code-18/tree/main/m2det
M2Det: A Single-Shot Object Detector based on Multi-Level Feature Pyramid Network
https://github.com/2023-MindSpore-1/ms-code-181
Side-Aware Boundary Localization for More Precise Object Detection
https://github.com/2023-MindSpore-1/ms-code-182
https://github.com/2023-MindSpore-1/ms-code-183
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/2023-MindSpore-1/ms-code-185
https://github.com/2023-MindSpore-1/ms-code-186
https://github.com/2023-MindSpore-1/ms-code-189/tree/main/modelarts
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/2023-MindSpore-1/ms-code-19
https://github.com/2023-MindSpore-1/ms-code-191
https://github.com/2023-MindSpore-1/ms-code-194
https://github.com/2023-MindSpore-1/ms-code-195
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/2023-MindSpore-1/ms-code-201
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.