https://github.com/MindSpore-paper-code-3/code8/tree/main/detr
DN-DETR: Accelerate DETR Training by Introducing Query DeNoising
Papers with Code 아카이브
2D Classification
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/MindSpore-paper-code-3/code8/tree/main/efficientnet-b0
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/MindSpore-paper-code-3/code8/tree/main/fairmot
FairMOT: On the Fairness of Detection and Re-Identification in Multiple Object Tracking
https://github.com/MindSpore-paper-code-3/code8/tree/main/faster_rcnn_dcn
https://github.com/MindSpore-paper-code-3/code9/tree/main/CycleGAN
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/MindSpore-paper-code-3/code9/tree/main/DYR
DyRA: Portable Dynamic Resolution Adjustment Network for Existing Detectors
https://github.com/MindSpore-paper-code-3/code9/tree/main/DeepLabv3
Rethinking Atrous Convolution for Semantic Image Segmentation
https://github.com/MindSpore-paper-code-3/code9/tree/main/Efficientnet
https://github.com/MindSpore-paper-code-3/code9/tree/main/FasterRCNN
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/MindSpore-paper-code-3/code9/tree/main/MaskRCNN
https://github.com/MindSpore-paper-code-3/code9/tree/main/OpenPose
OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
https://github.com/MindSpore-paper-code-3/code9/tree/main/ResNet
Rethinking Atrous Convolution for Semantic Image Segmentation
https://github.com/MindSpore-paper-code-3/code9/tree/main/SSD
https://github.com/MindSpore-paper-code-3/code9/tree/main/ShuffleNet
ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
https://github.com/MindSpore-scientific-2/code-10/tree/main/STCrowd
STCrowd: A Multimodal Dataset for Pedestrian Perception in Crowded Scenes
https://github.com/MindSpore-scientific-2/code-10/tree/main/SV-X-Softmax
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
https://github.com/MindSpore-scientific-2/code-10/tree/main/VAE-Creative-Discovery-using-QD-Search
VAE based Text Style Transfer with Pivot Words Enhancement Learning
https://github.com/MindSpore-scientific-2/code-10/tree/main/ZoneoutRNN
VAE based Text Style Transfer with Pivot Words Enhancement Learning
https://github.com/MindSpore-scientific-2/code-11/tree/main/STCrowd
STCrowd: A Multimodal Dataset for Pedestrian Perception in Crowded Scenes
https://github.com/MindSpore-scientific-2/code-11/tree/main/pixelshuffle1d
PixelShuffler: A Simple Image Translation Through Pixel Rearrangement
https://github.com/MindSpore-scientific-2/code-12/tree/main/KPC-cF-main
KPCA-CAM: Visual Explainability of Deep Computer Vision Models using Kernel PCA
https://github.com/MindSpore-scientific-2/code-12/tree/main/group-normalization
https://github.com/MindSpore-scientific-2/code-14/tree/main/groupvit
GroupViT: Semantic Segmentation Emerges from Text Supervision
https://github.com/MindSpore-scientific-2/code-14/tree/main/internlm
https://github.com/MindSpore-scientific-2/code-14/tree/main/mamba
Mamba YOLO: A Simple Baseline for Object Detection with State Space Model
https://github.com/MindSpore-scientific-2/code-2/tree/main/SING
https://github.com/MindSpore-scientific-2/code-3/tree/main/Sub2Full-OCT-Denoising
https://github.com/MindSpore-scientific-2/code-3/tree/main/WaveCRN-master
Wave-ViT: Unifying Wavelet and Transformers for Visual Representation Learning
https://github.com/MindSpore-scientific-2/code-4/tree/main/Deformable_Patch_Representation
https://github.com/MindSpore-scientific-2/code-4/tree/main/MicAugment
https://github.com/MindSpore-scientific-2/code-4/tree/main/PolyLoss
PolyLoss: A Polynomial Expansion Perspective of Classification Loss Functions
https://github.com/MindSpore-scientific-2/code-4/tree/main/fisheradversarial-mindspore
Robust and Accurate Object Detection via Adversarial Learning
https://github.com/MindSpore-scientific-2/code-4/tree/main/pixelshuffle1d
PixelShuffler: A Simple Image Translation Through Pixel Rearrangement
https://github.com/MindSpore-scientific-2/code-4/tree/main/rand_conv-master
RandAugment: Practical automated data augmentation with a reduced search space
https://github.com/MindSpore-scientific-2/code-5/tree/main/Deformable_Patch_Representation
https://github.com/MindSpore-scientific-2/code-5/tree/main/PolyLoss
PolyLoss: A Polynomial Expansion Perspective of Classification Loss Functions
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.