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/ooooverflow/BiSeNet

BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation

https://github.com/oorrppp2/darknet-pose

YOLO9000: Better, Faster, Stronger

https://github.com/opconty/keras-shufflenetV2

ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design

https://github.com/open-edge-platform/geti

Mask R-CNN

https://github.com/open-edge-platform/training_extensions

Mask R-CNN

https://github.com/open-mmlab/mmaction2

Non-local Neural Networks

https://github.com/open-mmlab/mmclassification

Deep Residual Learning for Image Recognition

https://github.com/open-mmlab/mmpose

Deep Residual Learning for Image Recognition

https://github.com/open-mmlab/mmpretrain

RandAugment: Practical automated data augmentation with a reduced search space

https://github.com/open-mmlab/mmsegmentation

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/open-mmlab/mmselfsup

Dense Contrastive Learning for Self-Supervised Visual Pre-Training

https://github.com/open-mmlab/mmsr

Deformable Convolutional Networks

https://github.com/open-mmlab/mmyolo

PP-YOLOE: An evolved version of YOLO

https://github.com/openai/cleverhans

Towards Deep Learning Models Resistant to Adversarial Attacks

https://github.com/opencv/openvino_training_extensions

SSD: Single Shot MultiBox Detector

https://github.com/openrobotlab/ov_parts

A Simple Baseline for Open-Vocabulary Semantic Segmentation with Pre-trained Vision-language Model

https://github.com/openvinotoolkit/openvino_xai

ViT-ReciproCAM: Gradient and Attention-Free Visual Explanations for Vision Transformer

https://github.com/optimalscale/detgpt

DetGPT: Detect What You Need via Reasoning

https://github.com/orobix/retina-unet

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/osilab-kaist/komet-benchmark-dataset

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/oskyhn/CNNs-Without-Borders

Deep Residual Learning for Image Recognition

https://github.com/osmr/imgclsmob

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/otamajakusi/darknet-yolov4

YOLOv3: An Incremental Improvement

https://github.com/oublalkhalid/AI-OpenPose

Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields

https://github.com/oulin1031esti/detect

Training-Time-Friendly Network for Real-Time Object Detection

https://github.com/oulutan/Drone_FasterRCNN

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

https://github.com/ouyanghuiyu/Thundernet_Pytorch

ThunderNet: Towards Real-time Generic Object Detection

https://github.com/overshiki/unet-pytorch

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/owena11/papers

Non-local Neural Networks

https://github.com/oxygen0605/ImageClassification

Deep Residual Learning for Image Recognition

https://github.com/oyeabhijit/yolo-obj-detection

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/ozora-ogino/efficient_backbones

HarDNet: A Low Memory Traffic Network

https://github.com/p-mc-grath/DMMFODS

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/p2irc/UDA4POC

Global Wheat Head Detection (GWHD) dataset: a large and diverse dataset of high resolution RGB labelled images to develop and benchmark wheat head detection methods

https://github.com/p517332051/GAN-Knowledge-Distillation-SSD

Distilling Object Detectors with Fine-grained Feature Imitation

https://github.com/pablodz/deblurgan

DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks

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