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/2023-MindSpore-1/ms-code-215/tree/main/ProtoNet
Improving ProtoNet for Few-Shot Video Object Recognition: Winner of ORBIT Challenge 2022
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/ResidualAttentionNet
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/simclr
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/2023-MindSpore-4/Code-5/tree/main/googlenet
https://github.com/2023-MindSpore-4/Code11/tree/main/simclr
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/2023-MindSpore-4/Code12/tree/main/MindFormers/clip
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/2023-MindSpore-4/Code14/tree/main/ResidualAttentionNet
https://github.com/2023-MindSpore-4/Code2/tree/main/DeepID
https://github.com/2023-MindSpore-4/Code6/tree/main/ResidualAttentionNet
https://github.com/2024-MindSpore-1/Code2/tree/main/model-1/clip
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/2024-MindSpore-1/Code6/tree/main/3D_DenseNet
https://github.com/63days/SimCLR
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/96jonesa/StyleGan2-Colab-Demo
https://github.com/A-PolarBear/GoogLeNet
https://github.com/AIOSYM/dl-model-gallery
https://github.com/Abhisek-/AlexNet
https://github.com/Adren98/EczemaApp
https://github.com/AhsanAliLodhi/curriculum_learning_blenderproc
https://github.com/AidenDurrant/MoCo-Pytorch
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/AirBernard/DenseNet-by-Pytorch
https://github.com/AlKun25/ResCon
https://github.com/AlbertoSabater/Robust-and-efficient-post-processing-for-video-object-detection
Robust and Efficient Post-Processing for Video Object Detection (REPP)
https://github.com/AlexSzen/wwf_shark_id
https://github.com/AlexandreMahdhaoui/fast-layers
https://github.com/AlexandreMahdhaoui/fast_layers
https://github.com/AliBahri94/SVWA_TTA
https://github.com/Anchoret13/blenderset
https://github.com/AndresPMD/Clip_CMR
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/AndrewAtanov/simclr-pytorch
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/Aniket7/Transfer-Learning
DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition
https://github.com/Aniket84/Object-Recognition-
https://github.com/Anil1331/DenseNet
https://github.com/AnindKiran/Object-Recognition-Using-CNNs
https://github.com/ApexPredator1/DenseNet_tensorflow
https://github.com/ArifRaihan/Deeper-CNN-Architectures-for-Image-Classification
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.