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Object

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Replace the cat with a British Shorthair cat of the breed with bulging yellow eyes

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/stefan-ainetter/grasp_det_seg_cnn

Depth-aware Object Segmentation and Grasp Detection for Robotic Picking Tasks

https://github.com/stephenharris/yolo-walkthrough

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

https://github.com/stevedepp/yolo4asl

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/stevensmiley1989/MrRobot

SSD: Single Shot MultiBox Detector

https://github.com/stevenzhou2017/MaskYolo

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

https://github.com/stevenzhou2017/darknet_AlexeyAB

YOLO9000: Better, Faster, Stronger

https://github.com/stevewongv/sparse2dense

AFDet: Anchor Free One Stage 3D Object Detection

https://github.com/stigma0617/maskrcnn-benchmark-vovnet

FCOS: Fully Convolutional One-Stage Object Detection

https://github.com/stomachcold/hctransformers

ImageNet Large Scale Visual Recognition Challenge

https://github.com/stupidZZ/pyc_repo

R-FCN: Object Detection via Region-based Fully Convolutional Networks

https://github.com/sty16/cell_mmdetection

Instances as Queries

https://github.com/subodh-malgonde/vehicle-detection

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

https://github.com/sudhakaranjain/3D_DEN

OrthographicNet: A Deep Transfer Learning Approach for 3D Object Recognition in Open-Ended Domains

https://github.com/sudharavali/objectDetectionYOLO

YOLO9000: Better, Faster, Stronger

https://github.com/sulasen/race-events-recognition-1

Focal Loss for Dense Object Detection

https://github.com/sunformoon/ObjectRecognitionWithWithoutObjects

Object Recognition with and without Objects

https://github.com/sung0471/pytorch-YOLOv4

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/sunhui1234/haha

https://github.com/sunlizhuang/YOLOv1-PaddlePaddle

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

https://github.com/sunqiangxtcsun/SSD

SSD: Single Shot MultiBox Detector

https://github.com/sunqiangxtcsun/faster-rcnn

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

https://github.com/sunshenggu/xc_eval_pcdet

From Points to Parts: 3D Object Detection from Point Cloud with Part-aware and Part-aggregation Network

https://github.com/super-wcg/Relation-Network-for-Object-Detection

Relation Networks for Object Detection

https://github.com/suraj-maniyar/Object-Tracking-SSD300

Fully-Convolutional Siamese Networks for Object Tracking

https://github.com/sushmaakoju/yolo

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/suvasis/birdnet2cs231n

TensorMask: A Foundation for Dense Object Segmentation

https://github.com/swaubhik/social-distance-detector

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

https://github.com/swift-n-brutal/syntex

Texture Synthesis Using Convolutional Neural Networks

https://github.com/symoon94/YOLO-keras

YOLO Nano: a Highly Compact You Only Look Once Convolutional Neural Network for Object Detection

https://github.com/syscv/ovtrack

Quasi-Dense Similarity Learning for Multiple Object Tracking

https://github.com/sysu-imsl/EdgeGAN

SketchyCOCO: Image Generation from Freehand Scene Sketches

https://github.com/sysu-imsl/SketchyCOCO

SketchyCOCO: Image Generation from Freehand Scene Sketches

https://github.com/t-hanya/kuzushiji-recognition

Objects as Points

https://github.com/taashi-s/M2Det_keras

M2Det: A Single-Shot Object Detector based on Multi-Level Feature Pyramid Network

https://github.com/taegoobot/aerial-object-detector

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

https://github.com/taeokimeng/object-detection-yolo

YOLOv4: Optimal Speed and Accuracy of Object Detection

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