| tinyvision/DAMO-YOLO |
3,598 |
|
0 |
0 |
over 2 years ago |
0 |
|
18 |
apache-2.0 |
Python |
| DAMO-YOLO: a fast and accurate object detection method with some new techs, including NAS backbones, efficient RepGFPN, ZeroHead, AlignedOTA, and distillation enhancement. |
| microsoft/Cream |
1,446 |
|
0 |
0 |
about 2 years ago |
0 |
|
16 |
mit |
Python |
| This is a collection of our NAS and Vision Transformer work. |
| VITA-Group/TENAS |
95 |
|
0 |
0 |
almost 5 years ago |
0 |
|
1 |
mit |
Python |
| [ICLR 2021] "Neural Architecture Search on ImageNet in Four GPU Hours: A Theoretically Inspired Perspective" by Wuyang Chen, Xinyu Gong, Zhangyang Wang |
| hunto/image_classification_sota |
58 |
|
0 |
0 |
about 2 years ago |
0 |
|
2 |
apache-2.0 |
Python |
| Training ImageNet / CIFAR models with sota strategies and fancy techniques such as ViT, KD, Rep, etc. |
| AberHu/TF-NAS |
52 |
|
0 |
0 |
almost 5 years ago |
0 |
|
3 |
mit |
Python |
| TF-NAS: Rethinking Three Search Freedoms of Latency-Constrained Differentiable Neural Architecture Search (ECCV2020) |
| researchmm/CyDAS |
28 |
|
0 |
0 |
about 4 years ago |
0 |
|
0 |
mit |
Python |
| Cyclic Differentiable Architecture Search |
| dongzelian/T-NAS |
27 |
|
0 |
0 |
over 3 years ago |
0 |
|
2 |
|
Python |
| Source code of ICLR2020 paper 'Towards Fast Adaptation of Neural Architectures with Meta Learning' |
| renqianluo/GBDT-NAS |
22 |
|
0 |
0 |
over 4 years ago |
0 |
|
1 |
mit |
Python |
| GBDT-NAS |
| guoyongcs/CNAS |
16 |
|
0 |
0 |
almost 4 years ago |
0 |
|
0 |
bsd-3-clause |
Python |
| Breaking the Curse of Space Explosion: Towards Efficient NAS with Curriculum Search |
| susan0199/StacNAS |
16 |
|
0 |
0 |
over 6 years ago |
0 |
|
4 |
|
Python |
