Image classification Models
There are 117 AI and NLP models for Image classification in our directory. Browse the full list below, or explore models by provider.
Image classification is the task of assigning category labels to images. We list 117 models for it.
Updated June 2026
- ADAM (CIFAR-10)Image classificationUniversity of Amsterdam,OpenAI,University of Toronto
- AlexNetImage classificationUniversity of Toronto
- ALIGNRepresentation learning,Image classification,Image representationGoogle Research
- AlphaX-1Neural architecture search for computer vision,Image classification,Object detection,Image captioningFacebook AI Research,Brown University
- BASIC-LImage classificationGoogle
- BASIC-L + LionImage classificationGoogle,University of California Los Angeles (UCLA)
- BatchNormImage classificationGoogle
- BEIT-3Object detection,Semantic segmentation,Image classification,Visual question answering,Image captioning,Language generationMicrosoft
- Big-Little NetImage classification,Object recognitionIBM
- Big Transfer (BiT-L)Image classificationGoogle Brain
- BLSTM for handwriting (1)Character recognition (OCR),Image classificationUniversity of Bern,IDSIA,Technical University of Munich
- CNN Committee (MNIST)Image classificationIDSIA
- CNN Committee (NIST)Image classificationIDSIA
- CNN committee (traffic sign)Image classificationIDSIA
- CoAtNetImage classificationGoogle,Google Research,Google Brain
- CoCaImage classification,Visual question answering,Image captioningGoogle Research
- CognitronMiscellaneous image analysis,Image classificationBiological Cybernetics
- CPC v2Image completion,Object detection,Image classificationDeepMind,University of California (UC) Berkeley
- data2vec (vision)Image classificationMeta AI
- Deep rectifier networksImage classificationUniversity of Montreal / Université de Montréal
- Deeply-supervised netsImage classification,Digit recognitionMicrosoft Research
- DeiT-BImage classificationMeta AI,Sorbonne University
- Denoising AutoencodersImage classificationUniversity of Montreal / Université de Montréal
- DenseNet-264Image classificationTsinghua University,Facebook AI Research,Cornell University
- DeticObject detection,Image classificationMeta AI,University of Texas at Austin
- DINOv2Image representation,Image classificationFacebook AI Research,INRIA
- DistBelief VisionImage classificationGoogle
- DL scaling ImageImage classificationBaidu
- DLDL (PASCAL)Image classificationUniversity of Oxford
- Dropout (ImageNet)Image classificationUniversity of Toronto
- Dropout: SVHNImage classification,Digit recognitionUniversity of Toronto
- EfficientNet-L2Image classificationGoogle
- EfficientNetV2-XLImage classification,Neural Architecture Search - NASGoogle,Google Brain
- Elastic weight consolidationImage classification,AtariDeepMind
- Error PropagationText classification,Image classificationUniversity of California San Diego,Carnegie Mellon University (CMU)
- EVA-01Image classification,Object detection,Semantic segmentation,Video classificationBeijing Academy of Artificial Intelligence / BAAI,Huazhong University of Science and Technology,Zhejiang University (ZJU),Beijing Institute of Technology
- EXAONE Path 2.0Cancer diagnosis,Image classification,Medical diagnosisLG AI Research
- FixRes ResNeXt-101 WSLImage classificationFacebook AI
- FlorenceImage captioning,Visual question answering,Image classification,Object detectionMicrosoft
- Fractional Max-PoolingImage classificationUniversity of Warwick
- GAN-AdvancerImage classificationOpenAI
- GoogLeNet / InceptionV1Image classificationGoogle,University of Michigan,University of North Carolina
- Greedy layer-wise DNN trainingImage classification,RegressionUniversity of Montreal / Université de Montréal
- High Performance CNN (NORB)Image classificationIDSIA,SUPSI
- ImageBindImage classification,Speech recognition (ASR),Image generation,Language modeling/generationMeta AI
- Inception-ResNet-V2Image classificationGoogle
- Inception v3Image classificationGoogle,University College London (UCL)
- Inceptionv4Image classificationGoogle
- InternImageImage classification,Object detection,Image segmentationShanghai AI Lab,Tsinghua University,Nanjing University,SenseTime,Chinese University of Hong Kong (CUHK)
- JFTImage classification,Object detection,Semantic segmentation,Pose estimationGoogle Research,Carnegie Mellon University (CMU)
- LaNet-L (CIFAR-10)Image classification,Neural Architecture Search - NASBrown University,Facebook
- Local Binary Patterns for facial recognitionImage classificationUniversity of Oulu,IEEE
- MADALINE IText classification,Image classificationStanford University
- Masked Autoencoders ViT-HSemantic segmentation,Image classification,Image generationFacebook AI Research
- Meta Pseudo LabelsImage classificationGoogle Brain,Google AI
- Mixture of linear modelsImage classification
- MLP baggage detectorImage classificationScience Applications International Corporation / SAIC
- MobileNetObject detection,Image classification,Face detectionGoogle
- MobileNetV2Object detection,Image classification,Image segmentationGoogle
- MSRA (C, PReLU)Image classificationMicrosoft Research
- NASNet-AImage classificationGoogle Brain
- NASv3 (CIFAR-10)Image classification,Neural Architecture Search - NASGoogle Brain
- Network in NetworkImage classificationNational University of Singapore
- Noisy Student (L2)Image classificationCarnegie Mellon University (CMU),Google
- OmniVecImage classification,Speech recognition (ASR)TensorTour
- Once for AllImage classificationMIT-IBM Watson AI Lab,Massachusetts Institute of Technology (MIT),IBM
- ONE-PEACEImage classification,Speech recognition (ASR),Audio question answering,Audio classification,Semantic segmentationAlibaba,Huazhong University of Science and Technology
- OR-WideResNetImage classificationDuke University,University of Chinese Academy of Sciences
- OverFeatImage classificationNew York University (NYU)
- Perceptron (1960)Image classificationCornell Aeronautical Laboratory
- Piecewise linear modelImage classificationUniversity of Kansas
- PolyNetImage classificationChinese University of Hong Kong (CUHK)
- Pooling CNN (Caltech 101)Image classificationUniversity of Bonn
- Pooling CNN (NORB)Image classificationUniversity of Bonn
- Prototypical networksImage classificationUniversity of Toronto,Twitter
- PyramidNetImage classificationKorea Advanced Institute of Science and Technology (KAIST)
- RBM Image ClassifierImage classificationUniversity of Toronto
- ResNet-1001Image classificationMicrosoft
- ResNet-101 (ImageNet)Image classificationMicrosoft
- ResNet-110 (CIFAR-10)Image classificationMicrosoft
- ResNet-152 (ImageNet)Image classificationMicrosoft
- ResNet-200Image classificationMicrosoft Research Asia
- ResNeXt-101 32x48dImage classificationFacebook
- ResNeXt-101 (64×4d)Image classificationUniversity of California San Diego,Facebook
- ResNeXt-101 Billion-scaleImage classificationFacebook AI
- ResNeXt-50Image classificationUniversity of California San Diego,Facebook
- SEERImage embedding,Image classificationFacebook AI Research,INRIA
- SENet (ImageNet)Image classificationChinese Academy of Sciences,University of Oxford
- SexNet classificationImage classification
- ShuffleNet v1Object detection,Image classificationMegvii Inc
- Siamese-TDNNImage classificationBell Laboratories
- SigLIP 400MImage classification,Image embeddingGoogle DeepMind
- SimpleNetImage classificationSensifai,Islamic Azad University,Technicolor R&I,Institute for Research in Fundamental Sciences (IPM)
- Sparse digit recognition SVMImage classificationUniversity of Lubeck
- Spatial Pyramid MatchingImage classificationINRIA,University of Illinois Urbana-Champaign (UIUC),Ecole Normale Supèrieure
- Spatially-Sparse CNNImage classificationUniversity of Warwick
- SPPNetImage classificationMicrosoft,Xi’an Jiaotong University,University of Science and Technology of China (USTC)
- SqueezeNetImage classificationDeepScale,University of California (UC) Berkeley,Stanford University
- Stacked Denoising AutoencodersImage classificationUniversity of Montreal / Université de Montréal,University of Toronto
- Statistical Shape ConstellationsImage classificationCalifornia Institute of Technology
- Super-vector codingImage classification,Object recognitionUniversity of Illinois Urbana-Champaign (UIUC),NEC Laboratories,Rutgers University
- Support Vector MachinesImage classificationAT&T,Bell Laboratories
- SVM-CNNImage classificationNew York University (NYU)
- Swin Transformer V2 (SwinV2-G)Action recognition,Image classificationMicrosoft Research Asia
- TCN (P-MNIST)Image classification,Digit recognitionCarnegie Mellon University (CMU),Intel Labs
- Transformer local-attention (NesT-B)Image classification,Image generationGoogle Cloud,Google Research
- Two Stage Feature Extraction (MNIST)Image classificationNew York University (NYU)
- Unsupervised High-level Feature LearnerImage classificationGoogle
- VGG16Image classificationUniversity of Oxford
- VGG19Image classificationUniversity of Oxford
- Visualizing CNNsImage classificationNew York University (NYU)
- ViT-22BObject detection,Image classificationGoogle
- ViT-G/14Image classificationGoogle Brain,Google Research
- ViT-G/14 (LiT)Image classificationGoogle Research
- ViT-G (model soup)Image classificationUniversity of Washington,Columbia University,Google,Meta AI,Tel Aviv University
- Wide Residual NetworkImage classificationUniversité Paris-Est
- XceptionImage classificationGoogle