A Japanese Conversation Dataset for Grounding Referential Expressions in Real-world Interactions

Multimodal reference resolution is crucial for human-assisting systems to understand user intentions and generate appropriate actions in the real world. The J-CRe3 dataset provides egocentric video, dialogue audio, and comprehensive annotations of textual and text-to-object reference relations to enable research on this task.