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코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/ColdNoodler/py-faster-rcnn-cuda10

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

https://github.com/Coldestadam/DynamicHead

Dynamic Head: Unifying Object Detection Heads with Attentions

https://github.com/Coldmooon/RCNN-for-Latest-Caffe

Rich feature hierarchies for accurate object detection and semantic segmentation

https://github.com/Coldmooon/SSD-on-Custom-Dataset

SSD: Single Shot MultiBox Detector

https://github.com/Congpeiliang/yolo

YOLOv3: An Incremental Improvement

https://github.com/ConnorChristie/image-to-3d-bbox

3D Bounding Box Estimation Using Deep Learning and Geometry

https://github.com/CorentinMAG/SRGAN

Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network

https://github.com/CorneliusHsiao/FoodMethodGAN

Deep Residual Learning for Image Recognition

https://github.com/Cosmos218/ssd-caffe

SSD: Single Shot MultiBox Detector

https://github.com/CreativeCodingLab/DeepIllumination

Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network

https://github.com/CrossEntropy/Gesture-images-recognition-ResidualNetwork

Deep Residual Learning for Image Recognition

https://github.com/CryptoSalamander/pytorch_paper_implementation

Deep Residual Learning for Image Recognition

https://github.com/CuberrChen/STDCNet-Paddle

Rethinking BiSeNet For Real-time Semantic Segmentation

https://github.com/CuberrChen/VoxelNet

VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection

https://github.com/CuberrChen/efficientdet-paddle

EfficientDet: Scalable and Efficient Object Detection

https://github.com/CycloneBoy/PPDetectionPytorch

SSD: Single Shot MultiBox Detector

https://github.com/Cyprien0105/DataScience

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

https://github.com/D-X-Y/DXY-Projects/tree/master/MSPLD

Few-Example Object Detection with Model Communication

https://github.com/D-X-Y/ResNeXt-DenseNet

Deep Residual Learning for Image Recognition

https://github.com/D1vyansh/BodyJointDetection

Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields

https://github.com/DAMI211/srgan

Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network

https://github.com/DASHANANT/Video-Segmentation

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/DCASE-REPO/dcase2019_task2_baseline

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

https://github.com/DChaushev/Age-Gender-Recognition

Max-Margin Object Detection

https://github.com/DHZS/tf-deformable-conv-layer

Deformable Convolutional Networks

https://github.com/DHZS/tf-dropblock

DropBlock: A regularization method for convolutional networks

https://github.com/DIG-Beihang/OPIXray

Occluded Prohibited Items Detection: an X-ray Security Inspection Benchmark and De-occlusion Attention Module

https://github.com/DIUx-xView/xView2_first_place

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/DInesh1234-wq/tyredataset

YOLO9000: Better, Faster, Stronger

https://github.com/DLWK/EANet

Rethinking Atrous Convolution for Semantic Image Segmentation

https://github.com/DS4SD/DocLayNet

DocLayNet: A Large Human-Annotated Dataset for Document-Layout Analysis

https://github.com/DS4SD/docling

DocLayNet: A Large Human-Annotated Dataset for Document-Layout Analysis

https://github.com/DT42/BerryNet

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

https://github.com/DableUTeeF/keras-efficientnet

Deep Residual Learning for Image Recognition

https://github.com/DaiJianBo/CenterNet-duan-2080Ti

CenterNet: Keypoint Triplets for Object Detection

https://github.com/DaikiTanak/manifold_mixup

Deep Residual Learning for Image Recognition

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.