/FGDA

For <An Adversarial Domain Adaptation Network for Cross-Domain Fine-Grained Recognition>

Primary LanguagePython

An Adversarial Domain Adaptation Network for Cross-Domain Fine-Grained Recognition

For WACV 2020 < An Adversarial Domain Adaptation Network for Cross-Domain Fine-Grained Recognition>, submission 564.

We add extra details of our paper in this repository containing the following aspects:

  • Experiments details and source codes,
  • Download MegRetail dataset and other two datasets.

Experiments details and source codes

We use PyTorch 1.0, CUDA 10.0 and Python 3.6 in all of our experiments. Tested on a 12CPU machine with 1xGPU NVIDIA GTX 1080Ti running Ubuntu 16 LTS.

Source Codes are available in ./Source_Codes.

Download MegRetail dataset and other two datasets

###MegRetail

MegRetail is a large-scale fine-grained dataset consisting of 52,011 images of 263 fine-grained classes from 3 domains.

Lately, MegRetail will be released here! We put some examples of MegRetail in ./MegRetail_Example.

###Office and GSV Cars

Also, for convenience, we provide the links of two dataset used in evaluation, Office and GSV Cars.

Office

GSV Cars