GraphFusion3D: Dynamic Graph Attention Convolution with Adaptive Cross-Modal Transformer for 3D Object Detection
Published:Dec 2, 2025 18:05
•1 min read
•ArXiv
Analysis
The article introduces GraphFusion3D, a novel approach for 3D object detection. It leverages dynamic graph attention convolution and an adaptive cross-modal transformer. The focus is on improving object detection performance in 3D environments by integrating different data modalities.
Key Takeaways
- •GraphFusion3D is a new method for 3D object detection.
- •It uses dynamic graph attention convolution.
- •It incorporates an adaptive cross-modal transformer.
- •The goal is to improve 3D object detection performance.
Reference
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