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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/CompVis/ipoke

iPOKE: Poking a Still Image for Controlled Stochastic Video Synthesis

https://github.com/CompVis/unsupervised-part-segmentation

Unsupervised Part-Based Disentangling of Object Shape and Appearance

https://github.com/Congpeiliang/yolo

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/ConnorChristie/image-to-3d-bbox

3D Bounding Box Estimation Using Deep Learning and Geometry

https://github.com/CosmiQ/yolt

YOLO9000: Better, Faster, Stronger

https://github.com/Cosmos218/ssd-caffe

SSD: Single Shot MultiBox Detector

https://github.com/CuberrChen/efficientdet-paddle

EfficientDet: Scalable and Efficient Object Detection

https://github.com/CycloneBoy/PPDetectionPytorch

SSD: Single Shot MultiBox Detector

https://github.com/D-X-Y/DXY-Projects/tree/master/MSPLD

Few-Example Object Detection with Model Communication

https://github.com/DChaushev/Age-Gender-Recognition

Max-Margin Object Detection

https://github.com/DInesh1234-wq/tyredataset

YOLO9000: Better, Faster, Stronger

https://github.com/DLR-RM/BlenderProc

BOP Challenge 2020 on 6D Object Localization

https://github.com/DLR-RM/instr

Unknown Object Segmentation from Stereo Images

https://github.com/DaiJianBo/CenterNet-duan-2080Ti

CenterNet: Keypoint Triplets for Object Detection

https://github.com/DaloroAT/first_break_picking

Focal Loss for Dense Object Detection

https://github.com/DataCanvasIO/Hypernets

MobileDets: Searching for Object Detection Architectures for Mobile Accelerators

https://github.com/DataXujing/EfficientDet_pytorch

EfficientDet: Scalable and Efficient Object Detection

https://github.com/DataXujing/ExtremeNet-Pytorch

Bottom-up Object Detection by Grouping Extreme and Center Points

https://github.com/DataXujing/TensorRT-DETR

End-to-End Object Detection with Transformers

https://github.com/DavianYang/yolo.ai

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

https://github.com/Dayan-Guan/DA-VSN

Uncertainty-Aware Unsupervised Domain Adaptation in Object Detection

https://github.com/DeLightCMU/MAL

Multiple Anchor Learning for Visual Object Detection

https://github.com/DeLightCMU/MAL-inference

Multiple Anchor Learning for Visual Object Detection

https://github.com/DeNA/Chainer_Mask_R-CNN

https://github.com/Deci-AI/super-gradients

SSD: Single Shot MultiBox Detector

https://github.com/Deep-Learner/Plot_CNNs_Python_Latex

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

https://github.com/DeepGraphLearning/GMNN

GMNN: Graph Markov Neural Networks

https://github.com/Deeplodocus/COCO-with-YOLO

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

https://github.com/Demonhesusheng/darknet_v2

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/DerrickGXD/unsupervised-keypoints

Unsupervised Learning of Object Keypoints for Perception and Control

https://github.com/DerrickXuNu/OpenCOOD

PIXOR: Real-time 3D Object Detection from Point Clouds

https://github.com/DetectionTeamUCAS/FCOS_GluonCV

FCOS: Fully Convolutional One-Stage Object Detection

https://github.com/DetectionTeamUCAS/FPN_Tensorflow

Feature Pyramid Networks for Object Detection

https://github.com/DetectionTeamUCAS/RetinaNet_Tensorflow_Rotation

Focal Loss for Dense Object Detection

https://github.com/DevBruce/YOLO-TF2

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

https://github.com/DevBruce/YOLOv1-TF2

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

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