| Convolutional Neural Networks (CNNs): |
|
| LeNet |
✅ |
| AlexNet |
✅ |
| VGG (VGG16, VGG19) |
|
| GoogleNet (Inception) |
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| ResNet (ResNet50, ResNet101) |
|
| Xception |
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| DenseNet |
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| EfficientNet |
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| MobileNet |
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| ShuffleNet |
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| SENet (Squeeze and Excitation Network) |
|
| SqueezeNet |
|
| RegNet |
|
| ConvNeXt |
|
| MixNet |
|
|
|
| Object Detection: |
|
| YOLO (You Only Look Once) |
|
| SSD (Single Shot MultiBox Detector) |
|
| R-CNN (Regions with CNN features) |
|
| Faster R-CNN |
|
| Mask R-CNN |
|
| RetinaNet |
|
| CenterNet |
|
| EfficientDet |
|
| YOLOv4, YOLOv5 |
|
| DETR (Detection Transformer) |
|
| FCOS (Fully Convolutional One-Stage Object Detection) |
|
|
|
| Pose Estimation: |
|
| 2D Pose Estimation (Heatmap-based methods) |
|
| Part-based models |
|
| Pictorial structures models |
|
| 3D Pose Estimation (PoseNet) |
|
| TPOT (Tree-based Pipeline Optimization Tool) |
|
| OpenPose |
|
| AlphaPose |
|
| DensePose |
|
| HRNet (High-Resolution Network for Pose Estimation) |
|
|
|
| Image Segmentation: |
|
| U-Net |
|
| DeepLab |
|
| DeepLabV3+ |
|
| Fully Convolutional Networks (FCNs) |
|
| Mask R-CNN |
|
| PSPNet (Pyramid Scene Parsing Network) |
|
| SegNet |
|
| BiSeNet (Bilateral Segmentation Network) |
|
| HRNet for Segmentation |
|
|
|
| Generative Algorithms and Network Architectures: |
|
| Variational Autoencoders (VAEs) |
|
| Pixel Recurrent Neural Networks (PixelRNN) |
|
| PixelCNN |
|
| BigGAN |
|
| StyleGAN2 |
|
| CycleGAN |
|
| SRGAN (Super-Resolution GAN) |
|
|
|
| Generative Adversarial Networks (GANs): |
|
| Conditional GANs (CGANs) |
|
| Wasserstein GANs (WGANs) |
|
| StyleGAN |
|
| ProGAN (Progressive Growing of GANs) |
|
| StarGAN (Multi-Domain Image-to-Image Translation) |
|
| Pix2Pix |
|
|
|
| Image Classification: |
|
| Capsule Networks |
|
| ResNeXt |
|
| Neural Architecture Search (NASNet) |
|
| Vision Transformers (ViT) |
|
| Swin Transformer |
|
| MLP-Mixer |
|
| ConvMixer |
|
| Hybrid Vision Transformers (Swin + CNNs) |
|
|
|
| Image Denoising: |
|
| Non-Local Means Denoising |
|
| Denoising Autoencoders (DAE) |
|
| BM3D (Block-Matching and 3D Filtering) |
|
|
|
| Image Super-Resolution: |
|
| Generative Adversarial Networks (GANs) |
|
| SRResNet (Super-Resolution ResNet) |
|
| Real-ESRGAN (Enhanced Super-Resolution GAN) |
|
|
|
| Deep Reinforcement Learning for Vision Tasks: |
|
| Deep Q-Networks (DQNs) |
|
|
|
| Optical Flow Estimation: |
|
| Farneback algorithm |
|
| PWC-Net (Pyramid, Warping, and Cost volume Network) |
|
| LiteFlowNet |
|
| RAFT (Recurrent All-Pairs Field Transforms) |
|
|
|
| Visual Object Tracking (VOT): |
|
| Kernelized Correlation Filters (KCF) |
|
| GOTURN (Generic Object Tracking Using Regression Networks) |
|
| SiamRPN (Siamese Region Proposal Network) |
|
| ByteTrack |
|
|
|
| Action Recognition: |
|
| Two-Stream Networks |
|
| 3D Convolutional Neural Networks (3D CNNs) |
|
| I3D (Inflated 3D ConvNet) |
|
| SlowFast Networks |
|
| TSM (Temporal Shift Module) |
|
|
|
| 3D Vision: |
|
| Structure from Motion (SfM) |
|
| Multi-View Stereo (MVS) |
|
| NeRF (Neural Radiance Fields) |
|
| PointNet |
|
| MeshCNN |
|
| Volumetric CNNs |
|
|
|
| Other Frameworks and Tools: |
|
| Darknet |
|
| VGGFace2 |
|
| OpenVINO |
|
| Detectron2 |
|
| MMDetection |
|
| mmdetection3d |
|
| OpenPose |
|