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.
no code implementations • CVPR 2023 • Qianli Feng, Raghudeep Gadde, Wentong Liao, Eduard Ramon, Aleix Martinez
We derive a method that yields highly accurate semantic segmentation maps without the use of any additional neural network, layers, manually annotated training data, or supervised training.
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.
no code implementations • 23 Feb 2022 • Qianli Feng, Viraj Shah, Raghudeep Gadde, Pietro Perona, Aleix Martinez
To edit a real photo using Generative Adversarial Networks (GANs), we need a GAN inversion algorithm to identify the latent vector that perfectly reproduces it.
no code implementations • 25 Jan 2022 • Guha Balakrishnan, Raghudeep Gadde, Aleix Martinez, Pietro Perona
We present a method for finding paths in a deep generative model's latent space that can maximally vary one set of image features while holding others constant.
1 code implementation • 12 Apr 2021 • Jeffrey Wen, Fabian Benitez-Quiroz, Qianli Feng, Aleix Martinez
Leveraging the learned structure of the latent space, we find moving in this direction corrects many image artifacts and brings the image into greater realism.
1 code implementation • 12 Nov 2020 • Stuart Synakowski, Qianli Feng, Aleix Martinez
In this paper, we derive an algorithm that can infer whether the behavior of an agent in a scene is intentional or unintentional based on its 3D kinematics, using the knowledge of self-propelled motion, Newtonian motion and their relationship.
1 code implementation • 1 May 2020 • Ciprian Corneanu, Meysam Madadi, Sergio Escalera, Aleix Martinez
Here, we derive an algorithm to estimate the performance gap between training and testing that does not require any testing dataset.
no code implementations • 28 Sep 2016 • Ruiqi Zhao, Yan Wang, Aleix Martinez
Three-dimensional shape reconstruction of 2D landmark points on a single image is a hallmark of human vision, but is a task that has been proven difficult for computer vision algorithms.