Papers with Code 아카이브

Object Detection

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

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/chonepieceyb/reading-frustum-pointnets-code

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

https://github.com/chongruo/detectron2-resnest

ResNeSt: Split-Attention Networks

https://github.com/chongweiliu/DUT-USEG

An Underwater Image Semantic Segmentation Method Focusing on Boundaries and a Real Underwater Scene Semantic Segmentation Dataset

https://github.com/chonyy/AI-basketball-analysis

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/chonyy/ML-auto-baseball-pitching-overlay

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/chouxianyu/Boundary-Aware-PoolNet

A Simple Pooling-Based Design for Real-Time Salient Object Detection

https://github.com/chowkamlee81/CentrePointNet

Center-based 3D Object Detection and Tracking

https://github.com/chrhenning/hypercl

Deep Residual Learning for Image Recognition

https://github.com/chris-boson/fashion_mnist

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/chrisqqq123/FA-Dist-EfficientNet

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

https://github.com/christiansafka/img2vec

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

https://github.com/christophmeyer/longboard-pothole-detection

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

https://github.com/chrisway613/MixConv

MixConv: Mixed Depthwise Convolutional Kernels

https://github.com/chrisway613/Synchronized-BatchNormalization

MegDet: A Large Mini-Batch Object Detector

https://github.com/chuanqichen/deepcoaching

Mask R-CNN

https://github.com/chuongngd/Images-Object-Detection

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

https://github.com/chwilms/sos

Learning Open-World Object Proposals without Learning to Classify

https://github.com/cihangxie/DAG

Adversarial Examples for Semantic Segmentation and Object Detection

https://github.com/cinastanbean/Pytorch-Multi-Task-Multi-class-Classification

Bag of Tricks for Image Classification with Convolutional Neural Networks

https://github.com/cioppaanthony/rt-sbs

Pyramid Scene Parsing Network

https://github.com/citbrains/darknet_yolov4

YOLOv3: An Incremental Improvement

https://github.com/cj-mclaughlin/segmentation_research

Deep Residual Learning for Image Recognition

https://github.com/cj4L/MST-python

https://github.com/cjf8899/KeepAugment_Pytorch

KeepAugment: A Simple Information-Preserving Data Augmentation Approach

https://github.com/cjfghk5697/Pytorch-Research-Paper-Implementations

Going Deeper with Convolutions

https://github.com/cjpurackal/m2det-tf

M2Det: A Single-Shot Object Detector based on Multi-Level Feature Pyramid Network

https://github.com/cjvargasc/YOLOv2

YOLO9000: Better, Faster, Stronger

https://github.com/ckyrkou/EmergencyNet

Searching for MobileNetV3

https://github.com/clairehester/face-mask-detector

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/clarencenhuang/dl-colorize

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/clasikman/darknet

YOLOv3: An Incremental Improvement

https://github.com/clavichord93/MENet

ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices

https://github.com/clbeggs/MobileSal

MobileSal: Extremely Efficient RGB-D Salient Object Detection

https://github.com/clemkoa/faster-rcnn

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

https://github.com/clemkoa/fasterrcnn

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

https://github.com/clemkoa/u-net

U-Net: Convolutional Networks for Biomedical Image Segmentation

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