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Kexin Yi

3 accepted papers

2022

ComPhy: Compositional Physical Reasoning of Objects and Events from Videos

ICLR 2022poster

Objects' motions in nature are governed by complex interactions and their properties. While some properties, such as shape and material, can be identified via the object's visual appearances, others like mass and electric charge are not directly visible. The compositionality between the visible and…

Cited by 58SourcePDFScholar
2020

Visual Grounding of Learned Physical Models

ICML 2020poster

Humans intuitively recognize objects’ physical properties and predict their motion, even when the objects are engaged in complicated interactions. The abilities to perform physical reasoning and to adapt to new environments, while intrinsic to humans, remain challenging to state-of-the-art computati…

Cited by 82SourcePDFScholar
2018

Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding

NeurIPS 2018spotlight

We marry two powerful ideas: deep representation learning for visual recognition and language understanding, and symbolic program execution for reasoning. Our neural-symbolic visual question answering (NS-VQA) system first recovers a structural scene representation from the image and a program trace…