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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/dhu-mmct/dhu-mmct

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

https://github.com/diksha0799/Image-Captioning-master

Microsoft COCO: Common Objects in Context

https://github.com/dimtziwnas/InHandScanningICCV15_GroundTruthViewer

3D Object Reconstruction from Hand-Object Interactions

https://github.com/dimtziwnas/InHandScanningICCV15_HandMotionViewer

3D Object Reconstruction from Hand-Object Interactions

https://github.com/dingjiansw101/RoITransformer_DOTA

Learning RoI Transformer for Detecting Oriented Objects in Aerial Images

https://github.com/dingwoai/FairMOT-BDD100K

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

https://github.com/dipu-bd/craft-moran-ocr

A Multi-Object Rectified Attention Network for Scene Text Recognition

https://github.com/dipuchak95/dip_net

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/dishen12/py03

Focal Loss for Dense Object Detection

https://github.com/diskhkme/VCONV_DAE_TF

VConv-DAE: Deep Volumetric Shape Learning Without Object Labels

https://github.com/divyam96/EESRGAN

Small-Object Detection in Remote Sensing Images with End-to-End Edge-Enhanced GAN and Object Detector Network

https://github.com/diyer22/bpycv

Training Deep Networks with Synthetic Data: Bridging the Reality Gap by Domain Randomization

https://github.com/djkim3/Yet-Another-EfficientDet-Pytorch

EfficientDet: Scalable and Efficient Object Detection

https://github.com/dmlc/gluon-cv/tree/master/gluoncv/model_zoo/smot

SMOT: Single-Shot Multi Object Tracking

https://github.com/dmonterom/face_recognition_TF2

Group Normalization

https://github.com/dmsi-ods/test-repo

Semantic Aware Attention Based Deep Object Co-segmentation

https://github.com/dnozza/profanity-obfuscation

YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors

https://github.com/doc-doc/NExT-OE

PaLI-X: On Scaling up a Multilingual Vision and Language Model

https://github.com/doheelab/pku-CenterNet

Objects as Points

https://github.com/dongkwonjin/eigenlanes

Eigencontours: Novel Contour Descriptors Based on Low-Rank Approximation

https://github.com/dongkyuk0419/YOLO

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

https://github.com/dongyangli-del/eeg_image_decode

Decoding Natural Images from EEG for Object Recognition

https://github.com/dorbodwolf/darknet

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/dragon20002/STLC_Server

YOLO9000: Better, Faster, Stronger

https://github.com/dreamercv/HSResNet-MMAL

Multi-branch and Multi-scale Attention Learning for Fine-Grained Visual Categorization

https://github.com/dreamway/CenterNet-objects-as-points

Objects as Points

https://github.com/drscotthawley/SPNet

YOLO9000: Better, Faster, Stronger

https://github.com/dtthi/darknetAlexeyAB

YOLO9000: Better, Faster, Stronger

https://github.com/dugusiqing/caffe

SSD: Single Shot MultiBox Detector

https://github.com/dvl-tum/mot_neural_solver

Tracking without bells and whistles

https://github.com/dvl-tum/motsynth-baselines

https://github.com/dvlab-research/3d-box-segment-anything

VoxelNeXt: Fully Sparse VoxelNet for 3D Object Detection and Tracking

https://github.com/dvlab-research/deepvision3d

Focal Sparse Convolutional Networks for 3D Object Detection

https://github.com/dvndra/car_detection_yolo

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

https://github.com/dvornikita/blitznet

BlitzNet: A Real-Time Deep Network for Scene Understanding

https://github.com/dwaithe/darknet3AB

YOLO9000: Better, Faster, Stronger

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