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Hierarchical Object-oriented Spatio-Temporal Reasoning for Video Question Answering ...
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Object-Centric Representation Learning for Video Question Answering ...
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Abstract:
Video question answering (Video QA) presents a powerful testbed for human-like intelligent behaviors. The task demands new capabilities to integrate video processing, language understanding, binding abstract linguistic concepts to concrete visual artifacts, and deliberative reasoning over spacetime. Neural networks offer a promising approach to reach this potential through learning from examples rather than handcrafting features and rules. However, neural networks are predominantly feature-based - they map data to unstructured vectorial representation and thus can fall into the trap of exploiting shortcuts through surface statistics instead of true systematic reasoning seen in symbolic systems. To tackle this issue, we advocate for object-centric representation as a basis for constructing spatio-temporal structures from videos, essentially bridging the semantic gap between low-level pattern recognition and high-level symbolic algebra. To this end, we propose a new query-guided representation framework to ... : Accepted by IJCNN 2021 ...
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Keyword:
Computer Vision and Pattern Recognition cs.CV; FOS Computer and information sciences
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URL: https://arxiv.org/abs/2104.05166 https://dx.doi.org/10.48550/arxiv.2104.05166
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Hierarchical Conditional Relation Networks for Multimodal Video Question Answering ...
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Hierarchical Conditional Relation Networks for Video Question Answering ...
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Teaching Chinese language and culture to Australian high school beginners through intercultural language teaching
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Ability of Dental Students to Deliver Oxygen in a Medical Emergency
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All the way with CDA: using critical discourse analysis to investigate the complexities of the classroom site
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