2020 cvpr Hierarchical Conditional Relation Networks for Video Question Answering

时间 2020-12-30

标签 VQA论文阅读 VideoQA CRN 繁體版

原文原文链接

摘要： problems：Video question answering (VideoQA) is challenging as it requires modeling capacity to distill dynamic visual artifacts and distant relations and to associate them with linguistic concepts

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1. Improved Neural Relation Detection for Knowledge Base Question Answering
2. Entity-Relation Extraction as Multi-turn Question Answering
3. Relation Networks for Object Detection [CVPR 2018]
4. Relation Distillation Networks for Video Object Detection
5. Appearance-and-Relation Networks for Video Classification
6. 论文解读：Hierarchical Question-Image Co-Attention for Visual Question Answering
7. VQA1-2016-Stacked Attention Networks for Image Question Answering
8. Visual Question Answering with Memory-Augmented Networks
9. Question-Guided Spatio-Temporal Contextual Attention for Video Question Answering 论文阅读笔记
10. CVPR 2020文本图像检测与识别论文/代码

>>更多相关文章<<