ZIL: Zero-shot Image-to-LiDAR Registration

arXiv:2609.22716 · cs.CV · Submitted 2026-09-19 · Read on arXiv

cs.CV

Submitted: 2026-09-19

Updated: 2026-09-19

Code: https://github.com/ZijunLi7/ZIL

Terminology

• Transformer — 18× in this paper · explained in 2 episodes
• Generalization — 12× in this paper · explained in 13 episodes
• Benchmark — 11× in this paper · explained in 2 episodes
• Accuracy — 7× in this paper · explained in 1 episode
• Conference on Computer Vision and Pattern Recognition — 7× in this paper
• Foundation Model — 7× in this paper · explained in 3 episodes
• Registration Recall — 6× in this paper
• Ablation — 5× in this paper · explained in 1 episode
• Ablation study — 3× in this paper · explained in 1 episode
• Adam — 3× in this paper · explained in 2 episodes
• Alignment — 3× in this paper · explained in 1 episode
• Embeddings — 3× in this paper · explained in 2 episodes
• Foundation Models — 3× in this paper · explained in 7 episodes
• Point Clouds — 3× in this paper · explained in 2 episodes
• Representation Learning — 3× in this paper · explained in 2 episodes
• Zero-Shot Generalization — 3× in this paper · explained in 5 episodes
• Adaptation — 2× in this paper · explained in 1 episode
• Calibration — 2× in this paper · explained in 7 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Multimodal Dataset — 2× in this paper · explained in 2 episodes
• Self-Supervised Learning — 2× in this paper · explained in 8 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Decode — 1× in this paper · explained in 2 episodes
• Diffusion Model — 1× in this paper · explained in 8 episodes
• Diffusion Models — 1× in this paper · explained in 6 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Distribution Shift — 1× in this paper · explained in 5 episodes
• Heterogeneous Graph — 1× in this paper · explained in 2 episodes
• Relative Rotation Error — 1× in this paper
• Relative Translation Error — 1× in this paper
• Self-Distillation — 1× in this paper · explained in 7 episodes
• Sparsity — 1× in this paper · explained in 4 episodes
• Transfer Learning — 1× in this paper · explained in 10 episodes
• Transferability — 1× in this paper · explained in 4 episodes
• Transformer Architecture — 1× in this paper · explained in 2 episodes

Sources

• nuScenes: A multimodal dataset for autonomous driving
• DepthLM: Metric Depth From Vision Language Models
• VLM3: Vision Language Models Are Native 3D Learners
• Boreas Road Trip: A Multi-Sensor Autonomous Driving Dataset on Challenging Roads
• DINOv2: Learning Robust Visual Features without Supervision

Related papers

• Loss Knows Best: Detecting Annotation Errors in Videos via Loss Trajectories
• AnchorWeave: World-Consistent Video Generation with Retrieved Local Spatial Memories
• Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift
• MambaX-Net: Dual-Input Mamba-Enhanced Cross-Attention Network for Longitudinal MRI Segmentation
• TeleOCR: Navigating Document Parsing Across Digital and Camera-Captured Documents
• A Survey on Efficient Vision-Language-Action Models