| VainF/DeepLabV3Plus-Pytorch |
1,010 |
|
0 |
0 |
over 3 years ago |
0 |
|
51 |
mit |
Python |
| Pretrained DeepLabv3 and DeepLabv3+ for Pascal VOC & Cityscapes |
| voldemortX/pytorch-auto-drive |
713 |
|
0 |
0 |
over 2 years ago |
0 |
|
30 |
bsd-3-clause |
Python |
| PytorchAutoDrive: Segmentation models (ERFNet, ENet, DeepLab, FCN...) and Lane detection models (SCNN, RESA, LSTR, LaneATT, BézierLaneNet...) based on PyTorch with fast training, visualization, benchmarking & deployment help |
| rishizek/tensorflow-deeplab-v3-plus |
637 |
|
0 |
0 |
about 6 years ago |
0 |
|
54 |
mit |
Python |
| DeepLabv3+ built in TensorFlow |
| sacmehta/ESPNetv2 |
375 |
|
0 |
0 |
about 5 years ago |
0 |
|
0 |
mit |
Python |
| A light-weight, power efficient, and general purpose convolutional neural network |
| sacmehta/EdgeNets |
340 |
|
0 |
0 |
over 4 years ago |
0 |
|
2 |
mit |
Python |
| This repository contains the source code of our work on designing efficient CNNs for computer vision |
| Haochen-Wang409/U2PL |
289 |
|
0 |
0 |
about 3 years ago |
0 |
|
0 |
apache-2.0 |
Python |
| [CVPR'22] Semi-Supervised Semantic Segmentation Using Unreliable Pseudo-Labels |
| voldemortX/DST-CBC |
106 |
|
0 |
0 |
almost 4 years ago |
0 |
|
4 |
bsd-3-clause |
Python |
| Implementation of our Pattern Recognition paper "DMT: Dynamic Mutual Training for Semi-Supervised Learning" |
| bethgelab/robust-detection-benchmark |
106 |
|
0 |
0 |
over 6 years ago |
0 |
|
1 |
mit |
Jupyter Notebook |
| Code, data and benchmark from the paper "Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming" (NeurIPS 2019 ML4AD) |
| lorenmt/reco |
78 |
|
0 |
0 |
about 4 years ago |
0 |
|
0 |
other |
Python |
| The implementation of "Bootstrapping Semantic Segmentation with Regional Contrast" [ICLR 2022]. |
| mitmul/chainer-pspnet |
76 |
|
0 |
0 |
over 7 years ago |
0 |
|
5 |
|
Python |
| PSPNet in Chainer |
