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/jasjeetIM/Mask-RCNN

Mask R-CNN

https://github.com/jason-hu7/PyTorch-YOLOv4

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/jason-su/UCGNet

CornerNet-Lite: Efficient Keypoint Based Object Detection

https://github.com/jason90330/EdgeFinal

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

https://github.com/javiergarciamolina/selfie-background-removal

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/jayin301/2021AutonomousACCar

YOLOv3: An Incremental Improvement

https://github.com/jbardelli/Petrographic-Image-Segmentation

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/jcheunglin/Full-Resolution-Residual-Networks-with-PyTorch

Full-Resolution Residual Networks for Semantic Segmentation in Street Scenes

https://github.com/jd730/OICR-pytorch

Multiple Instance Detection Network with Online Instance Classifier Refinement

https://github.com/jday96314/Kuzushiji

Deep Residual Learning for Image Recognition

https://github.com/jediofgever/PointNet_Custom_Object_Detection

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

https://github.com/jeffshih/autoTrain

PVANet: Lightweight Deep Neural Networks for Real-time Object Detection

https://github.com/jeffwiroj/robust_tutorial

Barlow Twins: Self-Supervised Learning via Redundancy Reduction

https://github.com/jellevankerk/Team-Challenge

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/jellywangjie/yolov3

YOLOv3: An Incremental Improvement

https://github.com/jendawkins/saliencySanity

Sanity Checks for Saliency Maps

https://github.com/jeong-tae/SNIP-filter-level-pytorch

SNIP: Single-shot Network Pruning based on Connection Sensitivity

https://github.com/jeongjin0/detector-cleanse

BadDet: Backdoor Attacks on Object Detection

https://github.com/jercas/TextBoxes_plusplus_tf

TextBoxes++: A Single-Shot Oriented Scene Text Detector

https://github.com/jerichooconnell/tf_unet

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/jeromepan/Image-motion-delbur-with-a-smart-phone-application

DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks

https://github.com/jeromerony/survey_wsl_histology/blob/6d98928a1da2c73d84a791a11a6f18acd647d9cd/mil/poolings/wildcat.py

https://github.com/jerry73204/mobilenet-v3-rs

Searching for MobileNetV3

https://github.com/jerrytony/mmdetection

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/jesperhauch/polynomial_deep_learning

Augmenting Deep Classifiers with Polynomial Neural Networks

https://github.com/jesse01/paddle-yolox

YOLOX: Exceeding YOLO Series in 2021

https://github.com/jessemelpolio/Faster_RCNN_for_DOTA

DOTA: A Large-scale Dataset for Object Detection in Aerial Images

https://github.com/jessychen1016/yolov3Onpytorch

YOLOv3: An Incremental Improvement

https://github.com/jewettaij/superpose3d

TEASER: Fast and Certifiable Point Cloud Registration

https://github.com/jfc4050/detect-to-track

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

https://github.com/jhaprince/multibully

Learning Transferable Visual Models From Natural Language Supervision

https://github.com/jhihan/rsna_pneumonia_detection

Mask R-CNN

https://github.com/jhkim-spa/FVNet_v2

Exploring Data Augmentation for Multi-Modality 3D Object Detection

https://github.com/jhoffman/lsda

LSDA: Large Scale Detection Through Adaptation

https://github.com/jhultman/PV-RCNN

PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection

https://github.com/jia-hao999/samba

VSCode: General Visual Salient and Camouflaged Object Detection with 2D Prompt Learning

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