SFE-VGGT: Source-Free VGGT Distillation for Event-Based Monocular Depth Estimation

arXiv:2609.36929 · cs.CV · Submitted 2026-09-29 · Read on arXiv

cs.CV

Submitted: 2026-09-29

Updated: 2026-09-29

Terminology

• Distillation — 58× in this paper · explained in 2 episodes
• Consistency — 11× in this paper · explained in 3 episodes
• Adaptation — 6× in this paper · explained in 1 episode
• Confidence-Weighted Depth Distillation — 6× in this paper
• Cross-Frame Relational Consistency — 6× in this paper
• Density-Aware Feature Distillation — 6× in this paper
• Foundation Model — 6× in this paper · explained in 3 episodes
• Transformer — 6× in this paper · explained in 2 episodes
• Foundation Models — 5× in this paper · explained in 7 episodes
• Generalization — 5× in this paper · explained in 13 episodes
• Ablation — 4× in this paper · explained in 1 episode
• Alignment — 4× in this paper · explained in 1 episode
• Knowledge Distillation — 4× in this paper · explained in 11 episodes
• Accuracy — 3× in this paper · explained in 1 episode
• Domain Shift — 3× in this paper · explained in 4 episodes
• Core — 2× in this paper · explained in 2 episodes
• Domain Adaptation — 2× in this paper · explained in 5 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Zero-Shot Generalization — 2× in this paper · explained in 5 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Active Regions — 1× in this paper · explained in 1 episode
• Multimodal Fusion — 1× in this paper · explained in 3 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Self-Supervised Learning — 1× in this paper · explained in 8 episodes
• Sparsity — 1× in this paper · explained in 4 episodes
• Temporal consistency — 1× in this paper · explained in 2 episodes

Sources

• EventVGGT: Exploring Cross-Modal Distillation for Consistent Event-based Depth Estimation
• Distilling the Knowledge in a Neural Network

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