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2D Classification

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하위 태스크

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코드

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

https://github.com/Mind23-2/MindCode-3

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/Mind23-2/MindCode-3/tree/main/HRNetW48_cls

Deep High-Resolution Representation Learning for Visual Recognition

https://github.com/Mind23-2/MindCode-3/tree/main/HRNetW48_seg

High-Resolution Representations for Labeling Pixels and Regions

https://github.com/Mind23-2/MindCode-3/tree/main/HireMLP

Hire-MLP: Vision MLP via Hierarchical Rearrangement

https://github.com/Mind23-2/MindCode-3/tree/main/I3D

Non-local Neural Networks

https://github.com/Mind23-2/MindCode-3/tree/main/ICNet

ICNet for Real-Time Semantic Segmentation on High-Resolution Images

https://github.com/Mind23-2/MindCode-3/tree/main/ISyNet

ISyNet: Convolutional Neural Networks design for AI accelerator

https://github.com/Mind23-2/MindCode-3/tree/main/LearningToSeeInTheDark

Learning to See in the Dark

https://github.com/Mind23-2/MindCode-3/tree/main/MAML

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

https://github.com/Mind23-2/MindCode-3/tree/main/NFNet

MaxViT: Multi-Axis Vision Transformer

https://github.com/Mind23-2/MindCode-3/tree/main/hlg

Vision Transformers: From Semantic Segmentation to Dense Prediction

https://github.com/Mind23-2/MindCode-3/tree/main/ibnnet

Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net

https://github.com/Mind23-2/MindCode-3/tree/main/lresnet100e_ir

Deep Residual Learning for Image Recognition

https://github.com/Mind23-2/MindCode-3/tree/main/m2det

M2Det: A Single-Shot Object Detector based on Multi-Level Feature Pyramid Network

https://github.com/Mind23-2/MindCode-3/tree/main/mnasnet

MnasNet: Platform-Aware Neural Architecture Search for Mobile

https://github.com/Mind23-2/MindCode-3/tree/main/mobilenetV3_small_x1_0

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

https://github.com/Mind23-2/MindCode-3/tree/main/mobilenetv3_large

Searching for MobileNetV3

https://github.com/Mind23-2/MindCode-3/tree/main/nas-fpn

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

https://github.com/Mind23-2/MindCode-3/tree/main/nasnet

MnasNet: Platform-Aware Neural Architecture Search for Mobile

https://github.com/Mind23-2/MindCode-33

Rethinking Atrous Convolution for Semantic Image Segmentation

https://github.com/Mind23-2/MindCode-36

EfficientDet: Scalable and Efficient Object Detection

https://github.com/Mind23-2/MindCode-37

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

https://github.com/Mind23-2/MindCode-39

Rethinking Atrous Convolution for Semantic Image Segmentation

https://github.com/Mind23-2/MindCode-4/tree/main/hrnet

Deep High-Resolution Representation Learning for Visual Recognition

https://github.com/Mind23-2/MindCode-42

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

https://github.com/Mind23-2/MindCode-43

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

https://github.com/Mind23-2/MindCode-46

FCOS: Fully Convolutional One-Stage Object Detection

https://github.com/Mind23-2/MindCode-47

FCOS: Fully Convolutional One-Stage Object Detection

https://github.com/Mind23-2/MindCode-5/tree/main/PSPNet

Pyramid Scene Parsing Network

https://github.com/Mind23-2/MindCode-5/tree/main/PVAnet

PVANet: Lightweight Deep Neural Networks for Real-time Object Detection

https://github.com/Mind23-2/MindCode-5/tree/main/pointpillars

Sparse PointPillars: Maintaining and Exploiting Input Sparsity to Improve Runtime on Embedded Systems

https://github.com/Mind23-2/MindCode-5/tree/main/pointtransformer

Point Transformer

https://github.com/Mind23-2/MindCode-5/tree/main/rcnn

RCNN-SliceNet: A Slice and Cluster Approach for Nuclei Centroid Detection in Three-Dimensional Fluorescence Microscopy Images

https://github.com/Mind23-2/MindCode-51

HarDNet: A Low Memory Traffic Network

https://github.com/Mind23-2/MindCode-52

Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net

https://github.com/Mind23-2/MindCode-53

ICNet for Real-Time Semantic Segmentation on High-Resolution Images

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