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.
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.
###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.