From Alignment to Fusion in 3D Vision-Language

arXiv:2609.28222 · cs.CV · Submitted 2026-09-23 · Read on arXiv

cs.CV

Submitted: 2026-09-23

Updated: 2026-09-23

Terminology

• Alignment — 42× in this paper · explained in 1 episode
• Grounding — 28× in this paper · explained in 3 episodes
• Visual Grounding — 15× in this paper · explained in 2 episodes
• Accuracy — 14× in this paper · explained in 1 episode
• Benchmark — 14× in this paper · explained in 2 episodes
• Adaptation — 13× in this paper · explained in 1 episode
• Instance Segmentation — 13× in this paper · explained in 3 episodes
• Conference on Computer Vision and Pattern Recognition — 11× in this paper
• Transformer — 11× in this paper · explained in 2 episodes
• Ablation — 8× in this paper · explained in 1 episode
• Point Clouds — 7× in this paper · explained in 2 episodes
• T RIPLE A LIGNMENT — 5× in this paper
• European Conference on Computer Vision — 4× in this paper
• International Conference on Computer Vision — 4× in this paper
• International Conference on Machine Learning — 4× in this paper
• Ablation study — 3× in this paper · explained in 1 episode
• Aggregation — 3× in this paper · explained in 1 episode
• Average Precision — 2× in this paper
• Embeddings — 2× in this paper · explained in 2 episodes
• Instruction Tuning — 2× in this paper · explained in 2 episodes
• Latent Space — 2× in this paper · explained in 7 episodes
• Multimodal Fusion — 2× in this paper · explained in 3 episodes
• 3D Gaussian Splatting — 1× in this paper · explained in 2 episodes
• Abstraction — 1× in this paper · explained in 1 episode
• Adaptive Fusion Mechanism — 1× in this paper · explained in 1 episode
• Affordance — 1× in this paper · explained in 1 episode
• Clustering — 1× in this paper · explained in 2 episodes
• Conference on Robot Learning — 1× in this paper
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Downstream Tasks — 1× in this paper · explained in 2 episodes
• Gaussian Splatting — 1× in this paper · explained in 4 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• THE RESULTS ARE REPORTED USING EXACT MATCH — 1× in this paper
• Task Planning — 1× in this paper · explained in 2 episodes

Sources

• The Replica Dataset: A Digital Replica of Indoor Spaces
• Proxy3D: Efficient 3D Representations for Vision-Language Models via Semantic Clustering and Alignment
• ISTR: End-to-End Instance Segmentation with Transformers
• Perceiver IO: A General Architecture for Structured Inputs & Outputs
• Cross Modal Transformer: Towards Fast and Robust 3D Object Detection
• Language Models are Few-Shot Learners

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