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approfondimento - 3D Visual Grounding
Semantic-Enhanced 3D Visual Grounding with Cross-modal Graph Attention
The author proposes SeCG, a semantic-enhanced relational learning model based on graph attention, to improve 3D visual grounding by addressing challenges in understanding multiple referred objects. The approach involves enhancing cross-modal alignment and leveraging prior semantic knowledge for better localization performance.
SeCG: Semantic-Enhanced 3D Visual Grounding via Cross-modal Graph Attention
提案されたSeCGは、複数の参照オブジェクトを含む記述の理解を向上させるために、グラフ注意力を活用した意味強化ビジュアルグラウンディングモデルです。
MiKASA: Multi-Key-Anchor & Scene-Aware Transformer for 3D Visual Grounding
MiKASA verbessert die Genauigkeit der Objekterkennung und das Verständnis räumlicher Beziehungen in 3D-Umgebungen.
Chain-of-Thoughts Data-Efficient 3D Visual Grounding Framework
A novel interpretable framework for 3D visual grounding that predicts a chain of anchor objects to localize the final target object, enhancing performance and data efficiency.
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