David_ding Attention Over Learned Object Embeddings Enables Complex Visual Reasoning 2021
Title: Attention Over Learned Object Embeddings Enables Complex Visual Reasoning Author: David Ding et. al. Publish Year: 2021 NeurIPS Review Date: Dec 2021 Background info for this paper: Their paper propose a all-in-one transformer model that is able to answer CLEVRER counterfactual questions with higher accuracy (75.6% vs 46.5%) and less training data (- 40%) They believe that their model relies on three key aspects: self-attention soft-discretization self-supervised learning What is self-attention...