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/nithinksath96/MMdetection_TensorRT_FP16

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/nithinksath96/mmdetection

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/nitin35/masktrackrcnn

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/nitz21/RoadDamage

Road Damage Detection Using Deep Neural Networks with Images Captured Through a Smartphone

https://github.com/niveditarahurkar/CS231N-ActionRecognition

TSM: Temporal Shift Module for Efficient Video Understanding

https://github.com/nkondapa/RSVC

Text-image Alignment for Diffusion-based Perception

https://github.com/nku-shengzheliu/PaddlePaddle-Swin-Transformer-V2

Swin Transformer V2: Scaling Up Capacity and Resolution

https://github.com/nlee-208/face_mask_detection

YOLOv3: An Incremental Improvement

https://github.com/nmcasasr/darknet2

YOLOv3: An Incremental Improvement

https://github.com/nmcasasr/darknet_oldVersion

YOLOv3: An Incremental Improvement

https://github.com/nnizhang/S2MA

https://github.com/nnizhang/VST

Visual Saliency Transformer

https://github.com/nnzzll/networks

UNet++: A Nested U-Net Architecture for Medical Image Segmentation

https://github.com/noelcodes/Mask_RCNN

Mask R-CNN

https://github.com/noelcodes/YOLO

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

https://github.com/noelcodes/cloth-recognition-version2

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

https://github.com/nolanliou/PeopleSegmentationDemo

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/nolanzzz/MTMCT

FairMOT: On the Fairness of Detection and Re-Identification in Multiple Object Tracking

https://github.com/noornk/U-Net

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/nope0124/ssd_keras_hisakawa

SSD: Single Shot MultiBox Detector

https://github.com/nopperl/clip_arxiv_pmc

Learning Transferable Visual Models From Natural Language Supervision

https://github.com/northeastsquare/effficientnet

Deep Residual Learning for Image Recognition

https://github.com/notha99y/mean_teacher_domain_adapt

Data Distillation: Towards Omni-Supervised Learning

https://github.com/notmariekondo/notmariekondo

YOLOP: You Only Look Once for Panoptic Driving Perception

https://github.com/noumannahmad/vehicle-detection-model-classifier-yolo3-python

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

https://github.com/novav/DetectoRS_Colab

DetectoRS: Detecting Objects with Recursive Feature Pyramid and Switchable Atrous Convolution

https://github.com/nqt228/YoloZ

YOLO-Z: Improving small object detection in YOLOv5 for autonomous vehicles

https://github.com/nram812/SuperResolutionSatellite

Spatial Frequency Loss for Learning Convolutional Autoencoders

https://github.com/nsarang/MnasNet

MnasNet: Platform-Aware Neural Architecture Search for Mobile

https://github.com/nsom/Basic-Models

Deep Residual Learning for Image Recognition

https://github.com/nsom/VGG16

Deep Residual Learning for Image Recognition

https://github.com/nsom/ssd

SSD: Single Shot MultiBox Detector

https://github.com/nsoul97/yolov1_pytorch

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

https://github.com/ntrin/CIFAR_10_ML

Deep Residual Learning for Image Recognition

https://github.com/nuaaceieyty/Paddle-YOLOv2

YOLO9000: Better, Faster, Stronger

https://github.com/nuaaceieyty/Paddle-YOLOv4

YOLOv4: Optimal Speed and Accuracy of Object Detection

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