Papers with Code 아카이브

2D Object Detection

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

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/HaoJunNM/Unet-PretrainedMobilenetV2encoder-Flaskapp

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/HaohanWang/ImageNet-Sketch

Learning Visual Representations for Transfer Learning by Suppressing Texture

https://github.com/HardLaugh/EfficientDet-bifpn

EfficientDet: Scalable and Efficient Object Detection

https://github.com/Hardly-Human/Yolo-Object-Detector

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/HarmanDotpy/Normalizations-in-Deep-Learning

Deep Residual Learning for Image Recognition

https://github.com/Harsh9524/AquaTrash

https://github.com/Harsharma2308/PoseRefinement

SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

https://github.com/Harut0726/my-pointnet-tensorflow

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

https://github.com/Harut0726/votenet

Deep Hough Voting for 3D Object Detection in Point Clouds

https://github.com/Hayashi-Yudai/ML_models

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/Hazqeel09/ellzaf_ml

Understanding the Role of the Projector in Knowledge Distillation

https://github.com/He-Zhenwei/MAF

Multi-adversarial Faster-RCNN for Unrestricted Object Detection

https://github.com/He-jerry/DSSNet

ResNeSt: Split-Attention Networks

https://github.com/He-jerry/U2Net-Tensorflow

U$^2$-Net: Going Deeper with Nested U-Structure for Salient Object Detection

https://github.com/HeapHop30/graph-attention-nets

Geometric deep learning on graphs and manifolds using mixture model CNNs

https://github.com/Hedgehogues/HoChiMinh

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/Heedeok/frustum-pointnets-rgbd

Frustum PointNets for 3D Object Detection from RGB-D Data

https://github.com/HeegonJin/yolov1

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/Helmholtz-AI-Energy/TBBRDet

https://github.com/HengWeiBin/CenterFusionDetect3D

CenterFusion: Center-based Radar and Camera Fusion for 3D Object Detection

https://github.com/HenonBamboo/PSPNet-MindSpore

Pyramid Scene Parsing Network

https://github.com/Hernandope/keras_resnet_FPN_cifar10

Feature Pyramid Networks for Object Detection

https://github.com/HiKapok/SSD.TensorFlow

SSD: Single Shot MultiBox Detector

https://github.com/HighCWu/stylegan2-paddle

Efficient Attention: Attention with Linear Complexities

https://github.com/HirataYurina/yoloV3-keras-sibyl

Weighted boxes fusion: Ensembling boxes from different object detection models

https://github.com/HirataYurina/yoloV4-keras-techi

Weighted boxes fusion: Ensembling boxes from different object detection models

https://github.com/HirataYurina/yolov4-tiny-keras

Weighted boxes fusion: Ensembling boxes from different object detection models

https://github.com/Hiwyl/mmdetection-obj

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/Hiwyl/yolov3-attentation

YOLOv3: An Incremental Improvement

https://github.com/HobbitLong/CMC

Unsupervised Feature Learning via Non-Parametric Instance-level Discrimination

https://github.com/HobbitLong/PyContrast

Self-Supervised Learning of Pretext-Invariant Representations

https://github.com/HoganZhang/FairMOT

FairMOT: On the Fairness of Detection and Re-Identification in Multiple Object Tracking

https://github.com/Holmes1204/PyTorch_Unet

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/HolmesShuan/AIM2020-RealSR

Going Deeper with Convolutions

https://github.com/Hong-Hyun-Seung/Mask_Classification

Bag of Tricks for Image Classification with Convolutional Neural Networks

https://github.com/HongSic/DarknetAI

YOLO9000: Better, Faster, Stronger

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