| jindongwang/transferlearning |
12,494 |
|
0 |
0 |
about 2 years ago |
0 |
|
14 |
mit |
Python |
| Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习 |
| thuml/Transfer-Learning-Library |
2,883 |
|
0 |
0 |
over 2 years ago |
2 |
July 24, 2020 |
28 |
mit |
Python |
| Transfer Learning Library for Domain Adaptation, Task Adaptation, and Domain Generalization |
| KaiyangZhou/Dassl.pytorch |
681 |
|
0 |
0 |
over 3 years ago |
0 |
|
9 |
mit |
Python |
| A PyTorch toolbox for domain generalization, domain adaptation and semi-supervised learning. |
| wasidennis/AdaptSegNet |
586 |
|
0 |
0 |
over 5 years ago |
0 |
|
13 |
|
Python |
| Learning to Adapt Structured Output Space for Semantic Segmentation, CVPR 2018 (spotlight) |
| easezyc/deep-transfer-learning |
517 |
|
0 |
0 |
about 4 years ago |
0 |
|
0 |
mit |
Python |
| A collection of implementations of deep domain adaptation algorithms |
| cs-chan/Exclusively-Dark-Image-Dataset |
461 |
|
0 |
0 |
over 2 years ago |
0 |
|
8 |
bsd-3-clause |
MATLAB |
| Exclusively Dark (ExDARK) dataset which to the best of our knowledge, is the largest collection of low-light images taken in very low-light environments to twilight (i.e 10 different conditions) to-date with image class and object level annotations. |
| KevinMusgrave/powerful-benchmarker |
426 |
|
0 |
0 |
over 2 years ago |
34 |
September 19, 2020 |
3 |
|
Jupyter Notebook |
| A library for ML benchmarking. It's powerful. |
| pykale/pykale |
415 |
|
0 |
0 |
about 2 years ago |
12 |
April 12, 2022 |
9 |
mit |
Python |
| Knowledge-Aware machine LEarning (KALE): accessible machine learning from multiple sources for interdisciplinary research, part of the 🔥PyTorch ecosystem. ⭐ Star to support our work! |
| thuml/Xlearn |
409 |
|
0 |
0 |
about 5 years ago |
0 |
|
20 |
|
Jupyter Notebook |
| Transfer Learning Library |
| CVLAB-Unibo/Real-time-self-adaptive-deep-stereo |
377 |
|
0 |
0 |
almost 4 years ago |
0 |
|
16 |
apache-2.0 |
Python |
| Code for "Real-time self-adaptive deep stereo" - CVPR 2019 (ORAL) |
