most citedGlobal and Local Features through Gaussian Mixture Models on Image Semantic Segmentation

7 citations · 11 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2023

Representation Learning via Consistent Assignment of Views over Random Partitions

Thalles Silva, Adín Ramírez Rivera

We present Consistent Assignment of Views over Random Partitions (CARP), a self-supervised clustering method for representation learning of visual features. CARP learns prototypes…

cs.CV2023

Self-supervised Learning of Contextualized Local Visual Embeddings

Thalles Santos Silva, Helio Pedrini, Adín Ramírez Rivera

We present Contextualized Local Visual Embeddings (CLoVE), a self-supervised convolutional-based method that learns representations suited for dense prediction tasks. CLoVE deviate…

cs.CV2023

SelfGraphVQA: A Self-Supervised Graph Neural Network for Scene-based Question Answering

Bruno Souza, Marius Aasan, Helio Pedrini +1

The intersection of vision and language is of major interest due to the increased focus on seamless integration between recognition and reasoning. Scene graphs (SGs) have emerged a…

cs.CV20227 cited

Global and Local Features through Gaussian Mixture Models on Image Semantic Segmentation

Darwin Saire, Adín Ramírez Rivera

The semantic segmentation task aims at dense classification at the pixel-wise level. Deep models exhibited progress in tackling this task. However, one remaining problem with these…

cs.LG20224 cited

RepFair-GAN: Mitigating Representation Bias in GANs Using Gradient Clipping

Patrik Joslin Kenfack, Kamil Sabbagh, Adín Ramírez Rivera +1

Fairness has become an essential problem in many domains of Machine Learning (ML), such as classification, natural language processing, and Generative Adversarial Networks (GANs).…