Papers with Code 아카이브
Object Recognition
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 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/atom06/Tiny_Faces_in_Tensorflow_v2
https://github.com/automl/pybnn
https://github.com/axit54/Object-Recognition-using-the-All-CNN-network
https://github.com/ayushpatidar/PR1-DenseNet
https://github.com/azima-fariha/DeepLearning_DenselyConnectedConvolutionalNetworks
https://github.com/azshue/TPT
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/balshersingh10/Object-Recognition
https://github.com/bamos/densenet.pytorch
https://github.com/basile-bron/Artificial-Intelligence-Bible
https://github.com/basile-bron/Artificial-Intelligence-Lexical
https://github.com/baskargroup/Arboretum
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/baskargroup/biotrove
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/bcmi/phdnet-painterly-image-harmonization
https://github.com/belaalb/TI-DG
https://github.com/belaalb/g2dm
https://github.com/bennyqp/artificial-inspiration
https://github.com/beresandras/contrastive-classification-keras
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/bespontaneous/proteus-pytorch
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/bethgelab/InDomainGeneralizationBenchmark
https://github.com/bfortuner/pytorch_tiramisu
https://github.com/bhaskar-gaur/DenseNet-Keras
https://github.com/bhuyanamit986/FlowerClassification
https://github.com/billyshin/CNN-Object-Recognition
https://github.com/bjader/QSSL
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/black0017/3D-GAN-pytorch
Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling
https://github.com/boris127/vehicle-detection
https://github.com/borisdayma/clip-jax
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/bozliu/E2E-Keyword-Spotting
https://github.com/brainimageanalysis/marmosetgeneatlas_adult
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/brian-moser/dartsrenet
ReNet: A Recurrent Neural Network Based Alternative to Convolutional Networks
https://github.com/brown-palm/ObjectPrompt
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/bruthyu/bpt-vlm
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/buyeah1109/KEN
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/buyeah1109/finc
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/caesarea38/doclangid
A Simple Framework for Contrastive Learning of Visual Representations
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.