Papers with visual dialog models
CLEVR-Dialog: A Diagnostic Dataset for Multi-Round Reasoning in Visual Dialog (N19-1)
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| Challenge: | Visual Dialog is a multimodal task of answering a sequence of questions grounded in an image. |
| Approach: | They construct a dialog grammar that is grounded in the scene graphs of the images from the CLEVR dataset and use it to benchmark performance of standard visual dialog models. |
| Outcome: | The proposed model is based on a large diagnostic dataset for studying multi-round reasoning in visual dialog. |
Learning to Ground Visual Objects for Visual Dialog (2021.findings-emnlp)
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| Challenge: | Existing methods to ground visual objects are inadequate for visual dialog . a posterior distribution is inferred from context and questions, while posterior distributions are used to facilitate visual objects grounding. |
| Approach: | They propose a method to learn to ground visual objects for visual dialog using prior and posterior distributions over visual objects to facilitate visual objects grounding. |
| Outcome: | The proposed approach improves the existing models in generative and discriminative settings by a significant margin. |