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/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

https://github.com/jiajunhua/Duankaiwen-CenterNet

CenterNet: Keypoint Triplets for Object Detection

https://github.com/jiajunhua/facebookresearch-Detectron

Fast R-CNN

https://github.com/jiama843/tf-YOLO-pascalVOC

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

https://github.com/jiama843/tf-mnist

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

https://github.com/jiandai/mlTst

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/jiangbestone/DetectRCNN

Rich feature hierarchies for accurate object detection and semantic segmentation

https://github.com/jiangbestone/DetectRccn

Rich feature hierarchies for accurate object detection and semantic segmentation

https://github.com/jiangbestone/detect_rcnn

Rich feature hierarchies for accurate object detection and semantic segmentation

https://github.com/jiangwx/SkyNet-ZCU104

FPGA/DNN Co-Design: An Efficient Design Methodology for IoT Intelligence on the Edge

https://github.com/jianing-sun/Mask-YOLO

YOLO9000: Better, Faster, Stronger

https://github.com/jianmingwuhasco/yolov3

YOLOv3: An Incremental Improvement

https://github.com/jianrenw/Self-Supervised-3D-Data-Association

Uncertainty-aware Self-supervised 3D Data Association

https://github.com/jiaowoguanren0615/MambaVision

MambaVision: A Hybrid Mamba-Transformer Vision Backbone

https://github.com/jiaruixu/st-cgan

Stacked Conditional Generative Adversarial Networks for Jointly Learning Shadow Detection and Shadow Removal

https://github.com/jiaxu-Zhu/DETR

End-to-End Object Detection with Transformers

https://github.com/jichengYUAN/mmdetectionCust

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/jiean001/models_m/tree/main/EGnet

https://github.com/jiggles546/60499_Project

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

https://github.com/jih189/yolo3

YOLOv3: An Incremental Improvement

https://github.com/jihaoxuanye/MetaPRD

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

https://github.com/jihoojo03/UNet-CBAM_Keras

Squeeze-and-Excitation Networks

https://github.com/jimheaton/Ultra96_ML_Embedded_Workshop

Going Deeper with Convolutions

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