LR-V2X: Loss-Resilient Collaborative Perception under Low-Bandwidth Communication

arXiv:2610.11264 · cs.CV · Submitted 2026-10-08 · Read on arXiv

cs.CV

Submitted: 2026-10-08

Updated: 2026-10-08

Code: https://github.com/sidiangongyuan/LR-V2X

Terminology

• Robustness — 16× in this paper · explained in 5 episodes
• Transformer — 10× in this paper · explained in 2 episodes
• Ablation — 9× in this paper · explained in 1 episode
• Diffusion Model — 9× in this paper · explained in 8 episodes
• Latent Prior Decoder — 9× in this paper
• Computer Vision and Pattern Recognition — 8× in this paper
• Benchmark — 5× in this paper · explained in 2 episodes
• Diffusion Models — 5× in this paper · explained in 6 episodes
• Late Fusion — 5× in this paper · explained in 2 episodes
• Redundancy — 4× in this paper · explained in 2 episodes
• Accuracy — 3× in this paper · explained in 1 episode
• Adam — 3× in this paper · explained in 2 episodes
• Distribution Shift — 3× in this paper · explained in 5 episodes
• Point Clouds — 3× in this paper · explained in 2 episodes
• Regularization — 3× in this paper · explained in 3 episodes
• Alignment — 2× in this paper · explained in 1 episode
• Communication Overhead — 2× in this paper · explained in 2 episodes
• Distillation — 2× in this paper · explained in 2 episodes
• IEEE International Conference on Robotics and Automation — 2× in this paper
• Mask Generation — 2× in this paper · explained in 2 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Consistency — 1× in this paper · explained in 3 episodes
• Cooperation — 1× in this paper · explained in 2 episodes
• Domain Adaptation — 1× in this paper · explained in 5 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Graceful Degradation — 1× in this paper · explained in 2 episodes
• Latent Diffusion Model — 1× in this paper · explained in 2 episodes
• Latent Diffusion Models — 1× in this paper · explained in 2 episodes
• Model-Agnostic — 1× in this paper · explained in 2 episodes
• Multi-Agent System — 1× in this paper · explained in 6 episodes

Sources

• ILVR: Conditioning Method for Denoising Diffusion Probabilistic Models
• Domain Adaptation for Visual Applications: A Comprehensive Survey
• STAMP: Scalable Task And Model-agnostic Collaborative Perception
• CoDiff: Conditional Diffusion Model for Collaborative 3D Object Detection
• An Extensible Framework for Open Heterogeneous Collaborative Perception
• Denoising Diffusion Implicit Models
• CoCMT: Communication-Efficient Cross-Modal Transformer for Collaborative Perception
• BM2CP: Efficient Collaborative Perception with LiDAR-Camera Modalities
• QuantV2X: A Fully Quantized Multi-Agent System for Cooperative Perception
• Pragmatic Heterogeneous Collaborative Perception via Generative Communication Mechanism

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