Papers with Code 아카이브

Object Recognition

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법 전체 데이터셋

하위 태스크: 3
평가표: 9
보존된 평가 기록: 31

Object recognition is a computer vision technique for detecting + classifying objects in images or videos. Since this is a combined task of object detection plus image classification, the state-of-the-art tables are recorded for each component task here and here.

<span style="color:grey; opacity: 0.6">( Image credit: Tensorflow Object Detection API )</span>

코드

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

https://github.com/ArmanAfrasiyabi/associative-alignment-fs

Associative Alignment for Few-shot Image Classification

https://github.com/Asteur/relation-network

Relation Networks for Object Detection

https://github.com/Asthestarsfalll/DenseNet-MegEngine

Densely Connected Convolutional Networks

https://github.com/AwesumMe/RetailClassification

The Freiburg Groceries Dataset

https://github.com/Bakikii/stylegan2-pytorch23

Efficient Attention: Attention with Linear Complexities

https://github.com/BalajiAI/SimCLR

A Simple Framework for Contrastive Learning of Visual Representations

https://github.com/BasileBron/Artificial-Intelligence-Lexical

Striving for Simplicity: The All Convolutional Net

https://github.com/Booomshaker/SparseRCNNWSL

Sparse R-CNN: End-to-End Object Detection with Learnable Proposals

https://github.com/BordiaS/layoutlm

Cutting the Error by Half: Investigation of Very Deep CNN and Advanced Training Strategies for Document Image Classification

https://github.com/Bribak/DeepConnection

Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition

https://github.com/ByakuyaUncia/DenseNetUncia

Densely Connected Convolutional Networks

https://github.com/CeLaMbDa/DenseNet_keras

Densely Connected Convolutional Networks

https://github.com/Celsuss/Residual_Attention_Network_for_Image_Classification

Residual Attention Network for Image Classification

https://github.com/Ciprian95/Licenta

Densely Connected Convolutional Networks

https://github.com/Cjl-MedSeg/DenseNet

Densely Connected Convolutional Networks

https://github.com/Contamination-Classification/DenseNet

Densely Connected Convolutional Networks

https://github.com/ContinualAI/avalanche

Memory Aware Synapses: Learning what (not) to forget

https://github.com/Crazy-Jack/PredNet

Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning

https://github.com/CyberPegasus/KUKA_Catch_Project

SegICP: Integrated Deep Semantic Segmentation and Pose Estimation

https://github.com/CycloneBoy/PPDetectionPytorch

RTMDet: An Empirical Study of Designing Real-Time Object Detectors

https://github.com/DaikiTanak/manifold_mixup

Densely Connected Convolutional Networks

https://github.com/Daniel-H-99/SimCLR

A Simple Framework for Contrastive Learning of Visual Representations

https://github.com/Deci-AI/super-gradients

Going Deeper with Convolutions

https://github.com/DeepTrial/Retina-VesselNet

Densely Connected Convolutional Networks

https://github.com/DentanJeremie/adversarialTransferts

Task-generalizable Adversarial Attack based on Perceptual Metric

https://github.com/Di-Is/stylegan2-ada-pytorch

Efficient Attention: Attention with Linear Complexities

https://github.com/DirtyHarryLYL/HAKE

HAKE: A Knowledge Engine Foundation for Human Activity Understanding

https://github.com/DmitryUlyanov/texture_nets

Texture Synthesis Using Convolutional Neural Networks

https://github.com/Duplums/bhb10k-dl-benchmark

Densely Connected Convolutional Networks

https://github.com/DylanMuir/fmin_adam

Improving neural networks by preventing co-adaptation of feature detectors

https://github.com/EMalagoli92/OD-Metrics

Microsoft COCO: Common Objects in Context

https://github.com/EdinCitaku/ANN-notebooks

Machine learning with neural networks

https://github.com/EkdeepSLubana/OrthoReg

Faster gaze prediction with dense networks and Fisher pruning

https://github.com/Eltomad/Tiny_Faces

Finding Tiny Faces

https://github.com/Elvictor01/Plant-Pathology-2020---FGVC7-Identify-the-category-of-foliar-diseases-in-apple-trees

Densely Connected Convolutional Networks

https://github.com/Emma0118/domain-generalization

Domain Generalization by Solving Jigsaw Puzzles

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