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2D Classification

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코드

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

https://github.com/MS-Mind/MS-Code-06/tree/main/PSPNet

Pyramid Scene Parsing Network

https://github.com/MS-Mind/MS-Code-06/tree/main/pointpillars

https://github.com/MS-Mind/MS-Code-06/tree/main/pointtransformer

Point Transformer

https://github.com/MS-Mind/MS-Code-08/tree/main/MIMO-UNet

UNet++: A Nested U-Net Architecture for Medical Image Segmentation

https://github.com/MS-Mind/MS-Code-08/tree/main/Non_local

Non-local Neural Networks

https://github.com/MS-Mind/MS-Code-08/tree/main/mnasnet

MnasNet: Platform-Aware Neural Architecture Search for Mobile

https://github.com/MS-Mind/MS-Code-08/tree/main/mobilenetV3_small_x1_0

Searching for MobileNetV3

https://github.com/MS-Mind/MS-Code-08/tree/main/mobilenetv3_large

Searching for MobileNetV3

https://github.com/MS-Mind/MS-Code-08/tree/main/nas-fpn

NAS-FPN: Learning Scalable Feature Pyramid Architecture for Object Detection

https://github.com/MS-P3/code3/tree/main/internlm

InternLM-XComposer: A Vision-Language Large Model for Advanced Text-image Comprehension and Composition

https://github.com/MS-P3/code4/tree/main/DECO

DECO: Query-Based End-to-End Object Detection with ConvNets

https://github.com/MS-P3/code4/tree/main/RCNN

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

https://github.com/MS-P3/code4/tree/main/SLAB

SLAB: Efficient Transformers with Simplified Linear Attention and Progressive Re-parameterized Batch Normalization

https://github.com/MS-P3/code7/tree/main/vitdet

Aerial Image Object Detection With Vision Transformer Detector (ViTDet)

https://github.com/MS-P3/code7/tree/main/yolos

DETRs Beat YOLOs on Real-time Object Detection

https://github.com/MSJawad/yolov3

YOLOv3: An Incremental Improvement

https://github.com/MSeeker1340/Vision2018-Pose

Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields

https://github.com/MTCloudVision/mxnet-dssd

SSD: Single Shot MultiBox Detector

https://github.com/MTG/music-ner

Recognizing Musical Entities in User-generated Content

https://github.com/MY-Swich/SOLO

SOLOv2: Dynamic and Fast Instance Segmentation

https://github.com/MY-Swich/SOLO_my

SOLOv2: Dynamic and Fast Instance Segmentation

https://github.com/MY-Swich/solo-len

SOLOv2: Dynamic and Fast Instance Segmentation

https://github.com/Machine-Learning-Tokyo/Poetry-GAN

Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context

https://github.com/MaczekO/AttentionNetworkProject

Attention Augmented Convolutional Networks

https://github.com/Madave94/VSR-TexBiG-Dataset

https://github.com/Madave94/kalphacv

https://github.com/Madhusakth/Adaptive-Radar-Acquisition

Automotive Radar Data Acquisition using Object Detection

https://github.com/MaheepChaudhary/Stand-Alone_Self-Attention

Stand-Alone Self-Attention in Vision Models

https://github.com/Makunda/DeepLearningASL

Mask R-CNN

https://github.com/Malik1998/VSTAM

https://github.com/Manan1811/Neural-Style-Transfer

A Neural Algorithm of Artistic Style

https://github.com/ManfredGonzalez/multispectral-pineapple-detection

EfficientDet: Scalable and Efficient Object Detection

https://github.com/ManoniLo/keras-YOLOv3-model-set__Fastest

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/ManooshSamiei/Object-Detection-Deep-Reinforcement-Learning

Object Detection with Deep Reinforcement Learning

https://github.com/ManthanBhala/Style-Transfer-by-Rigid-Alignment

Style Transfer by Rigid Alignment in Neural Net Feature Space

https://github.com/ManuMahadevaswamy/PEGASUS

Newsroom: A Dataset of 1.3 Million Summaries with Diverse Extractive Strategies

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