Papers with Code 아카이브

Object Detection

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전체 기법전체 데이터셋

하위 태스크

39

평가표

124

보존된 평가 기록

977

코드

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

https://github.com/Eric3911/ScaledYOLOv4

Scaled-YOLOv4: Scaling Cross Stage Partial Network

https://github.com/EricAlcaide/MiniFold

Deep Residual Learning for Image Recognition

https://github.com/EricYang3721/faces

SSD: Single Shot MultiBox Detector

https://github.com/ErickDiaz/bioinformatic_thesis_project

Applying Faster R-CNN for Object Detection on Malaria Images

https://github.com/ErikGDev/instance-segmentation

Mask R-CNN

https://github.com/EstherBear/implementation-of-pruning-filters

Deep Residual Learning for Image Recognition

https://github.com/EvaBr/AnatomyNets

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/Everina/car-detection-yolo

You Only Look Once: Unified, Real-Time Object Detection

https://github.com/EvgenyDyshlyuk/Oil_Seep_Detection

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/Expedit-LargeScale-Vision-Transformer/Expedit-SWAG

Expediting Large-Scale Vision Transformer for Dense Prediction without Fine-tuning

https://github.com/FL77N/Fast-RCNN-on-PPDet

Fast R-CNN

https://github.com/FL77N/RetinaNet-Based-on-PPdet

Focal Loss for Dense Object Detection

https://github.com/FMsunyh/keras-yolo2

YOLO9000: Better, Faster, Stronger

https://github.com/FaceOnLive/Face-Recognition-SDK-Android

Continual Forgetting for Pre-trained Vision Models

https://github.com/FaceOnLive/License-Plate-Recognition-SDK-Android

A Robust Real-Time Automatic License Plate Recognition Based on the YOLO Detector

https://github.com/FaceOnLive/Realtime-Background-Changer-SDK-Android

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/Factral/UnMix-NeRF

Designing BERT for Convolutional Networks: Sparse and Hierarchical Masked Modeling

https://github.com/FarihaHossain/SwinFSR

AM-RADIO: Agglomerative Vision Foundation Model -- Reduce All Domains Into One

https://github.com/FarzamIHPC/YoloV3_mask

YOLOv3: An Incremental Improvement

https://github.com/FateScript/CenterNet-better

Objects as Points

https://github.com/FayCai/framework

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/Fei-dong/SOLO_SORT

SOLOv2: Dynamic and Fast Instance Segmentation

https://github.com/FelixGruen/tensorflow-u-net

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/FenHua/Robust_Logo_Detection

DetectoRS: Detecting Objects with Recursive Feature Pyramid and Switchable Atrous Convolution

https://github.com/Feynman1999/MgeEditing

Tracking Objects as Points

https://github.com/Feynman27/pytorch-detect-rfcn

R-FCN: Object Detection via Region-based Fully Convolutional Networks

https://github.com/Feynman27/pytorch-detect-to-track

Detect to Track and Track to Detect

https://github.com/FicmillaR/FicmillaR.github.io

Weighted boxes fusion: Ensembling boxes from different object detection models

https://github.com/FlameRB/Face-Detection-using-Deep-Learning

Multi-view Face Detection Using Deep Convolutional Neural Networks

https://github.com/FloCF/SSL_pytorch

Barlow Twins: Self-Supervised Learning via Redundancy Reduction

https://github.com/FlorentijnD/FairMOT

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

https://github.com/FlorinAndrei/TensorAim

YOLOv3: An Incremental Improvement

https://github.com/FlowWind1999/pointnet-2

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

https://github.com/FluteXu/ms-project

RetinaMask: Learning to predict masks improves state-of-the-art single-shot detection for free

https://github.com/FlyEgle/MAE-pytorch

Masked Autoencoders Are Scalable Vision Learners

https://github.com/FlyingAnt2018/darknet-modify

YOLOv3: An Incremental Improvement

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