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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/lzccccc/3d-bounding-box-estimation-for-autonomous-driving

3D Bounding Box Estimation Using Deep Learning and Geometry

https://github.com/lzmisscc/emoran

A Multi-Object Rectified Attention Network for Scene Text Recognition

https://github.com/lzrobots/dgmn

FCOS: Fully Convolutional One-Stage Object Detection

https://github.com/lzx1413/CAFFE_SSD

SSD: Single Shot MultiBox Detector

https://github.com/m-parchami/3DVehicleDetection

3D Bounding Box Estimation Using Deep Learning and Geometry

https://github.com/machc/spherical_embeddings

Cross-Domain 3D Equivariant Image Embeddings

https://github.com/machine-learning-glossary/glossary

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

https://github.com/machines-in-motion/grasping_sim

Leveraging Contact Forces for Learning to Grasp

https://github.com/macomino/TFM

https://github.com/magicsunday/pico

Object Detection with Pixel Intensity Comparisons Organized in Decision Trees

https://github.com/magnificent1208/r3det-on-mmdetection

Focal Loss for Dense Object Detection

https://github.com/makarandtapaswi/Real2Sim_CoRL2020

Learning Object Manipulation Skills via Approximate State Estimation from Real Videos

https://github.com/makatx/YOLO_ResNet

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

https://github.com/makefile/frcnn

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

https://github.com/manankshastri/Object-Detection

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

https://github.com/manikandan-ravikiran/squeezeDet

SqueezeDet: Unified, Small, Low Power Fully Convolutional Neural Networks for Real-Time Object Detection for Autonomous Driving

https://github.com/manishravula/yolov3_tiny_pruned

YOLO9000: Better, Faster, Stronger

https://github.com/manishsoni1908/mobilenet-ssd-keras

SSD: Single Shot MultiBox Detector

https://github.com/manthanpatel2/Object-Detection-on-a-Frame

Microsoft COCO: Common Objects in Context

https://github.com/mappy/tf-faster-rcnn

Spatial Memory for Context Reasoning in Object Detection

https://github.com/marcusnerva/hmn

End-to-End Object Detection with Transformers

https://github.com/marinarierav-uab/foveabox

FoveaBox: Beyond Anchor-based Object Detector

https://github.com/markson14/WheatDet

FCOS: Fully Convolutional One-Stage Object Detection

https://github.com/martinruenz/maskfusion

MaskFusion: Real-Time Recognition, Tracking and Reconstruction of Multiple Moving Objects

https://github.com/masamitsu-murase/deform_conv2d_onnx_exporter

Deformable ConvNets v2: More Deformable, Better Results

https://github.com/mathiasroesler/machine_teaching

Striving for Simplicity: The All Convolutional Net

https://github.com/mathieuorhan/darknet

YOLO9000: Better, Faster, Stronger

https://github.com/matsui528/manga109api

Object Detection for Comics using Manga109 Annotations

https://github.com/mattfeng/recurrent-extreme-occlusion

Robustness of Object Recognition under Extreme Occlusion in Humans and Computational Models

https://github.com/matwilso/object_collections

Learning to Manipulate Object Collections Using Grounded State Representations

https://github.com/maudzung/CenterNet3D-PyTorch

Objects as Points

https://github.com/maudzung/Complex-YOLOv4-Pytorch

Complex-YOLO: Real-time 3D Object Detection on Point Clouds

https://github.com/maudzung/RTM3D

Objects as Points

https://github.com/maudzung/SFA3D

Objects as Points

https://github.com/maudzung/YOLO3D-YOLOv4-PyTorch

YOLO3D: End-to-end real-time 3D Oriented Object Bounding Box Detection from LiDAR Point Cloud

https://github.com/maudzung/super-fast-accurate-3d-object-detection

Objects as Points

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