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/Vonski/wdi19

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

https://github.com/WARM-3D/WARM-3D

WARM-3D: A Weakly-Supervised Sim2Real Domain Adaptation Framework for Roadside Monocular 3D Object Detection

https://github.com/WWangYuHsiang/SMILEtrack

SMILEtrack: SiMIlarity LEarning for Occlusion-Aware Multiple Object Tracking

https://github.com/WXinlong/DenseCL

Dense Contrastive Learning for Self-Supervised Visual Pre-Training

https://github.com/WYGNG/CenterNet-Pro

Objects as Points

https://github.com/WYGNG/USTC_SSE_Project

Objects as Points

https://github.com/WaelOuni/MergeTenserFlowWithOdb

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

https://github.com/Wakeupbuddy/amodalAPI

Semantic Amodal Segmentation

https://github.com/WalterMa/gluon-faster-rcnn

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

https://github.com/WangFeng18/Swin-Transformer

Swin Transformer: Hierarchical Vision Transformer using Shifted Windows

https://github.com/WangMian-Maker/Flask

YOLOv3: An Incremental Improvement

https://github.com/WangWenhao0716/Adapted-Center-and-Scale-Prediction

Adapted Center and Scale Prediction: More Stable and More Accurate

https://github.com/WangWenhao0716/DomainMix

Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net

https://github.com/WangY0906/mmdetection-for-study

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/Wangxy2180/darknetKinectDetect

YOLO9000: Better, Faster, Stronger

https://github.com/WangyiNTU/SCALNet

A Self-Training Approach for Point-Supervised Object Detection and Counting in Crowds

https://github.com/Wastoon/MOT-CenterNet

Weighted boxes fusion: Ensembling boxes from different object detection models

https://github.com/Wastoon/XinTong_CenterNet

Objects as Points

https://github.com/WaterScenes/Awesome-Water-Surface-Perception

WaterScenes: A Multi-Task 4D Radar-Camera Fusion Dataset and Benchmarks for Autonomous Driving on Water Surfaces

https://github.com/Watson-BCA/HumanPostureRecognition

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

https://github.com/WavesUR/embedded_TSM

Non-local Neural Networks

https://github.com/Will-J-Gale/Self-Driving-Car-Vision

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/Windxy/YOLOv4-Based-on-PaddleDetection

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/WinstonLy/Electricity-Inspection-Based-Ascend310

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/WonJunPark/Efficientnet

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

https://github.com/WordBearerYI/VoxelNet-pytorch

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

https://github.com/Wordbe/MobileNetV2

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/WuJiang1996/pytorch-YOLOv4

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/WuPedin/Multi-class_Yolov5_DeepSort_Pytorch

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/X-BrainLab/GTNet

GTNet: Generative Transfer Network for Zero-Shot Object Detection

https://github.com/XJTUWYD/TWN

Ternary Weight Networks

https://github.com/XXXVincent/SOLO

SOLOv2: Dynamic and Fast Instance Segmentation

https://github.com/XavierCHEN34/ClickSEG

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/Xephyrum/Agriculturice

Scalable Object Detection using Deep Neural Networks

https://github.com/Xephyrum/CropsMD

Scalable Object Detection using Deep Neural Networks

https://github.com/XiangGaofeng/MindSpore-SSD

SSD: Single Shot MultiBox Detector

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