Ioannis Marras — accepted AI-conference papers

2021

Poly-NL: Linear Complexity Non-Local Layers With 3rd Order Polynomials

Francesca Babiloni, Ioannis Marras, Filippos Kokkinos, Jiankang Deng, Grigorios Chrysos, Stefanos Zafeiriou

ICCV 2021poster

Spatial self-attention layers, in the form of Non-Local blocks, introduce long-range dependencies in Convolutional Neural Networks by computing pairwise similarities among all possible positions. Such pairwise functions underpin the effectiveness of non-local layers, but also determine a complexity…

Cited by 14 PDF ↗Scholar ↗

2020

Reconstructing the Noise Variance Manifold for Image Denoising

Ioannis Marras, Grigorios G. Chrysos, Ioannis Alexiou, Gregory Slabaugh, Stefanos Zafeiriou

ECCV 2020poster

Deep Convolutional Neural Networks (CNNs) have been successfully used in many low-level vision problems like image denoising. Although the conditional image generation techniques have led to large improvements in this task, there has been little effort in providing conditional generative adversarial…

Cited by 8 Source ↗PDF ↗Scholar ↗

2020

TESA: Tensor Element Self-Attention via Matricization

Francesca Babiloni, Ioannis Marras, Gregory Slabaugh, Stefanos Zafeiriou

CVPR 2020poster

Representation learning is a fundamental part of modern computer vision, where abstract representations of data are encoded as tensors optimized to solve problems like image segmentation and inpainting. Recently, self-attention in the form of Non-Local Block has emerged as a powerful technique to en…

Cited by 26 PDF ↗code ↗Scholar ↗

2017

Deep Globally Constrained MRFs for Human Pose Estimation

Ioannis Marras, Petar Palasek, Ioannis Patras

ICCV 2017poster

This work introduces a novel Convolutional Network architecture (ConvNet) for the task of human pose estimation, that is the localization of body joints in a single static image. We propose a coarse to fine architecture that addresses shortcomings of the baseline architecture in [26] that stem from…

Cited by 8 PDF ↗Scholar ↗