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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/NVlabs/PoseCNN-PyTorch

PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes

https://github.com/NVlabs/SCOPS

SCOPS: Self-Supervised Co-Part Segmentation

https://github.com/NVlabs/UnseenObjectClustering

Learning RGB-D Feature Embeddings for Unseen Object Instance Segmentation

https://github.com/NVlabs/contact_graspnet

Unknown Object Segmentation from Stereo Images

https://github.com/NVlabs/industreallib

https://github.com/NVlabs/latentfusion

LatentFusion: End-to-End Differentiable Reconstruction and Rendering for Unseen Object Pose Estimation

https://github.com/NaCl-Ocean/Anchor_free_detection_rotation

1st Place Solutions of Waymo Open Dataset Challenge 2020 -- 2D Object Detection Track

https://github.com/Nacriema/Loss-Functions-For-Semantic-Segmentation

Locating Objects Without Bounding Boxes

https://github.com/Nandu960/Road-Asset-Detection

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

https://github.com/NextVisionLab/egoism-hoi

Egocentric Human-Object Interaction Detection Exploiting Synthetic Data

https://github.com/Nicholasli1995/EgoNet

MonoPair: Monocular 3D Object Detection Using Pairwise Spatial Relationships

https://github.com/Nikhil619/Autonomous-driving-with-camera-using-Yolo

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

https://github.com/NiravRaiyani/Mask-R-CNN-for-water-detection

https://github.com/NonMagneticNeedle/vision.ai

Objects as Points

https://github.com/NovasMax/R3Det-Refined-Single-Stage-Detector-with-Feature-Refinement-for-RO

Focal Loss for Dense Object Detection

https://github.com/NumericalAdvantage/ld-node-facedetector-2

Max-Margin Object Detection

https://github.com/OFRIN/Tensorflow_FCOS

FCOS: Fully Convolutional One-Stage Object Detection

https://github.com/OFRIN/Tensorflow_GIoU

Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regression

https://github.com/OFRIN/Tensorflow_RetinaFace

Focal Loss for Dense Object Detection

https://github.com/OFRIN/Tensorflow_YOLOv1

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

https://github.com/Ohyeon5/MismatchPenaltySegmentation

SSD: Single Shot MultiBox Detector

https://github.com/Ohyeon5/MultiscaleSegmentation

SSD: Single Shot MultiBox Detector

https://github.com/Oishani/Machine-Learning-Projects

Striving for Simplicity: The All Convolutional Net

https://github.com/Okery/PyTorch-Simple-MaskRCNN

https://github.com/Omar-Awad/SCNN_GPU2

SBNet: Sparse Blocks Network for Fast Inference

https://github.com/OscarPellicer/prostate_lesion_detection

Retina U-Net: Embarrassingly Simple Exploitation of Segmentation Supervision for Medical Object Detection

https://github.com/OshriHalimi/precise_shape_completion

The Whole Is Greater Than the Sum of Its Nonrigid Parts

https://github.com/Oushesh/CapsulesforSegmentation

Capsules for Object Segmentation

https://github.com/Oushesh/SegCaps-TF_Version

Capsules for Object Segmentation

https://github.com/Oussamayousre/Yoga_pose_recognizer

Feature Pyramid Networks for Object Detection

https://github.com/OwlTing/AI_basketball_games_video_editor

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/PKU-EPIC/PartManip

PartManip: Learning Cross-Category Generalizable Part Manipulation Policy from Point Cloud Observations

https://github.com/POSTECH-CVLab/FastPointTransformer

Point Transformer

https://github.com/POSTECH-CVLab/point-transformer

Point Transformer

https://github.com/PaddlePaddle/PASSL

Dense Contrastive Learning for Self-Supervised Visual Pre-Training

https://github.com/PaddlePaddle/Paddle3D

PointPillars: Fast Encoders for Object Detection from Point Clouds

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