1 code implementation • 30 Apr 2024 • Chenqi Guo, Shiwei Zhong, Xiaofeng Liu, Qianli Feng, Yinglong Ma
By increasing data augmentation strengths, our key findings reveal a decrease in the Intersection over Union (IoU) of attentions between teacher models, leading to reduced student overfitting and decreased fidelity.
no code implementations • 8 Mar 2023 • Chenqi Guo, Fabian Benitez-Quiroz, Qianli Feng, Aleix Martinez
Our experiments on imbalanced image dataset classification show that, the validation accuracy improvement with such re-balancing method is related to the image similarity between different classes.
1 code implementation • ICCV 2021 • Qianli Feng, Chenqi Guo, Fabian Benitez-Quiroz, Aleix Martinez
With empirical evidence from BigGAN and StyleGAN2, on datasets CelebA, Flower and LSUN-bedroom, we show that dataset size and its complexity play an important role in GANs replication and perceptual quality of the generated images.