Computer Vision

Estimating label quality and errors in semantic segmentation data via any model

The soft-minimum of the model-estimated likelihoods of each pixel’s annotated class – that is particularly effective to identify images that are mislabeled, across multiple types of annotation error

GRUNet: A Novel Bi-directional RNN for VQA

We propose a new framework which we call GRUNet. GRUNet is a novel Bi-Directional RNN architecture that combines GRU + RNN + ResNet to effectively combine text and im- age input to answer VQA questions.