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/ZUCCBBQ/yoloV3-

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

https://github.com/ZXdatascience/TextDetectorAndroid

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/ZZR8066/mmdetection-GaofenCompetition

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/Zachdr1/CNNs

Deep Residual Learning for Image Recognition

https://github.com/ZackPashkin/YOLOv3-EfficientNet-EffYolo

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

https://github.com/ZackPashkin/text2cartoon-pytorch-CLIP

Learning Transferable Visual Models From Natural Language Supervision

https://github.com/Zahra2351373/Image-Processing-Final-Project

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/Zakobian/CT_framework_

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/Zanderzt/TensorRT_Mask_RCNN

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

https://github.com/ZeeTsing/Carvana_challenge

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/Zehaos/MobileNet

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

https://github.com/Zeng555/EMV-YOLO

Getting to Know Low-light Images with The Exclusively Dark Dataset

https://github.com/Zengyi-Qin/TLNet

Triangulation Learning Network: from Monocular to Stereo 3D Object Detection

https://github.com/ZhZiKai/VisDrone_FCOS

FCOS: Fully Convolutional One-Stage Object Detection

https://github.com/Zhang-Jing-Xuan/MaskRCNN

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

https://github.com/ZhangGongjie/CAD-Net

CAD-Net: A Context-Aware Detection Network for Objects in Remote Sensing Imagery

https://github.com/ZhangJiajun1995/cs231n-camp

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

https://github.com/Zhangyongtao123/maskrcnn_benchmark

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

https://github.com/ZhaoChuyang/trans-person-search

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/ZhenJie-Zhang/darknet_shoe

YOLO9000: Better, Faster, Stronger

https://github.com/ZhichengHuang/Food-Project

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

https://github.com/ZhihaoZhu/PointNet-Implementation-Tensorflow

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

https://github.com/ZhiqiWang12/try_darknet

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/ZhixinLai/3D-detection-with-monocular-RGB-image

3D Bounding Box Estimation Using Deep Learning and Geometry

https://github.com/ZhouKai90/face-detection-ssd-mxnet

SSD: Single Shot MultiBox Detector

https://github.com/Zhuoranbupt/ECE285fa19

YOLOv3: An Incremental Improvement

https://github.com/Zhz1997/Singing-voice-speration-with-U-Net

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/Zoky-2020/Set-level_Guidance_Attack

Towards Deep Learning Models Resistant to Adversarial Attacks

https://github.com/Zoushuang86/quiz_w8

SSD: Single Shot MultiBox Detector

https://github.com/ZyphonGT/TFLite-Frontier-Project-UPH

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

https://github.com/Zzh-tju/DIoU-SSD-pytorch

Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression

https://github.com/Zzh-tju/DIoU-darknet

Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression

https://github.com/Zzh-tju/DIoU-pytorch-detectron

Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression

https://github.com/Zzh-tju/ultralytics-YOLOv3-Cluster-NMS

YOLOv3: An Incremental Improvement

https://github.com/a-martyn/unet

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/a-nau/Plane-Segmentation-Refinement

Refined Plane Segmentation for Cuboid-Shaped Objects by Leveraging Edge Detection

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