Meta-repository for deep learning papers
Each implemented in PyTorch, Lightning or TensorFlow
Paper: MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
| Repository | Framework | Key Features |
|---|---|---|
| jungin500/mobilenetv1-tf | Tensorflow 2.x |
Paper: MobileNetV2: Inverted Residuals and Linear Bottlenecks
| Repository | Framework | Key Features |
|---|---|---|
| jungin500/mobilenetv2-torch | PyTorch | PyTorch Lightning, NVIDIA DALI |
Paper: Searching for MobileNetV3
| Repository | Branch (Revision) | Framework | Key Features |
|---|---|---|---|
| jungin500/mobilenetv3-torch | v1 | PyTorch | |
| jungin500/mobilenetv3-torch | v2 | PyTorch | tensorboard, docker |
| jungin500/mobilenetv3-rpi | PyTorch | Smaller model for RPi inference |
Paper: You Only Look Once: Unified, Real-Time Object Detection
| Repository | Branch (Revision) | Framework | Key Features |
|---|---|---|---|
| jungin500/yolov1-tf | Tensorflow 2.x | ||
| jungin500/yolov1-mobilenetv1-tf | Tensorflow 2.x | Custom backbone (MobileNetV1) | |
| jungin500/yolov1-torch | v1 | PyTorch | |
| jungin500/yolov1-torch | v2 | PyTorch | PyTorch Lightning |
Paper: YOLO9000: Better, Faster, Stronger
| Repository | Framework | Key Features |
|---|---|---|
| jungin500/yolov2-tf | Tensorflow 2.x |
Paper: YOLOv3: An Incremental Improvement
| Repository | Framework | Key Features |
|---|---|---|
| jungin500/yolov3-tf | Tensorflow 2.x |