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/PatriciaRodrigues1994/Satellite-Image-Segmentation

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/PatrickHua/SimpleMAE

Masked Autoencoders Are Scalable Vision Learners

https://github.com/PaulEmmanuelSotir/DeepCV

Pyramidal Convolution: Rethinking Convolutional Neural Networks for Visual Recognition

https://github.com/PaulGitt/ShuffleNetV2-tensorflow

ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design

https://github.com/PaulZhangIsing/CaffeSSD-opencv4

SSD: Single Shot MultiBox Detector

https://github.com/Pchank/caffe-sal

Amulet: Aggregating Multi-level Convolutional Features for Salient Object Detection

https://github.com/Pedestrian1671022/darknet

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/PenK1nG/DroneMOT

DroneMOT: Drone-based Multi-Object Tracking Considering Detection Difficulties and Simultaneous Moving of Drones and Objects

https://github.com/PengchengAi/tf-faster-rcnn-pcai

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

https://github.com/Pengchengzhi/Yolov3_Own-dataset

YOLOv3: An Incremental Improvement

https://github.com/Pepitaw/darknet

YOLOv3: An Incremental Improvement

https://github.com/PericlesPet/darknet-demo

YOLO9000: Better, Faster, Stronger

https://github.com/PeterTKovacs/zold137

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

https://github.com/PetersonSilvadeJesus/yolov3-data-images

YOLOv3: An Incremental Improvement

https://github.com/PettyDevil/caffe_ssd

SSD: Single Shot MultiBox Detector

https://github.com/PhanTom2003/PSPnet

Pyramid Scene Parsing Network

https://github.com/PhanTom2003/SSD

SSD: Single Shot MultiBox Detector

https://github.com/PierrickPochelu/word_tree_label

YOLO9000: Better, Faster, Stronger

https://github.com/Ping-C/CertifiedObjectDetection

Detection as Regression: Certified Object Detection by Median Smoothing

https://github.com/PingoLH/CenterNet-HarDNet

Objects as Points

https://github.com/PingoLH/FCHarDNet

HarDNet: A Low Memory Traffic Network

https://github.com/PiseyYou/MobileNet_Caffe_Configuration

SSD: Single Shot MultiBox Detector

https://github.com/PistonY/ResidualAttentionNetwork

Bag of Tricks for Image Classification with Convolutional Neural Networks

https://github.com/PlumedSerpent/tmp_perspective_map

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/PointsCoder/ONCE_Benchmark

One Million Scenes for Autonomous Driving: ONCE Dataset

https://github.com/PointsCoder/Pyramid-RCNN

Pyramid R-CNN: Towards Better Performance and Adaptability for 3D Object Detection

https://github.com/PointsCoder/VOTR

Voxel Transformer for 3D Object Detection

https://github.com/PolarisAlpha/darknet

YOLO9000: Better, Faster, Stronger

https://github.com/PolinaDruzhinina/mobilenet

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

https://github.com/PolinaDruzhinina/modelnet

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

https://github.com/PolinaYA/yolov3

YOLOv3: An Incremental Improvement

https://github.com/Popcorn-sugar/Deep_v2

Rethinking Atrous Convolution for Semantic Image Segmentation

https://github.com/Popoooo/darknet_test

YOLO9000: Better, Faster, Stronger

https://github.com/Poseidon0711/Autonomous-driving-application---Car-detection

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

https://github.com/PotatoSpudowski/CactiNet

MnasNet: Platform-Aware Neural Architecture Search for Mobile

https://github.com/Pranav21091996/Semantic_Fidelity-and-Egoshots

nocaps: novel object captioning at scale

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