4 accepted papers
Abstract visual reasoning (AVR) is a critical ability of humans, and it has been widely studied, but arithmetic visual reasoning, a unique task in AVR to reason over number sense, is less studied in the literature. To facilitate this research, we construct a Machine Number Reasoning (MNR) dataset to…
Most existing models for abstract visual reasoning perform poorly in compositional visual reasoning (CVR), due to complex nature of compositional rules and difficulties in distinguishing tiny rule differences between outliers and normal images. To tackle the challenges, we propose a Dual-Branch Comp…
Abstract Visual Reasoning (AVR) entails discerning latent patterns in visual data and inferring underlying rules. Existing solutions often lack scalability and adaptability, as deep architectures tend to overfit training data, and static neural networks fail to dynamically capture diverse rules. To…
Abstract Visual Reasoning (AVR) has been widely studied in literature. Our study reveals that AVR models tend to rely on appearance matching rather than a genuine understanding of underlying rules. We hence develop a challenging benchmark, Multiple Complex Compositional Reasoning (MC2R), composed of…