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🔗 Source: ijcai.org
📊 Size: 1.66 MB
👤 Author: Heng Wang, Chaoyi Zhang, Jianhui Yu, Weidong Cai
⬇️ Downloads: 266

Summary

Dense captioning in 3D point clouds involves object-level 3D scene understanding, aiming to produce natural language descriptions of objects in a scene. The proposed SpaCap3D method uses a transformer-based encoder-decoder architecture to transform objects into descriptions, focusing on relative spatiality of objects in 3D scenes. A spatiality-guided encoder is designed via a token-to-token spatial relation learning objective, and an object-centric decoder is used for precise object caption generation. Evaluated on ScanRefer and ReferIt3D datasets, SpaCap3D outperforms the baseline method Scan2Cap by 4.94% and 9.61% in [email protected], respectively.

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Description

Dense captioning in 3D point clouds involves object-level 3D scene understanding, aiming to produce natural language descriptions of objects in a scene.

Technical Information

  • File Format: PDF
  • File Size: 1.66 MB
  • Pages: 8
  • Language: EN
  • Author: Heng Wang, Chaoyi Zhang, Jianhui Yu, Weidong Cai
  • Total Downloads: 266
  • Last Updated: 2 hours ago

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