Dense Coverage, Sparse Refinement: Byte-Constrained Cooperative Perception

arXiv:2609.29456 · cs.CV · Submitted 2026-09-24 · Read on arXiv

cs.CV

Submitted: 2026-09-24

Updated: 2026-09-24

Terminology

• Quantization — 31× in this paper · explained in 12 episodes
• Accuracy — 20× in this paper · explained in 1 episode
• Adaptation — 10× in this paper · explained in 1 episode
• Ablation — 7× in this paper · explained in 1 episode
• Vector Quantization — 7× in this paper
• Benchmark — 6× in this paper · explained in 2 episodes
• Generalization — 5× in this paper · explained in 13 episodes
• Late Fusion — 5× in this paper · explained in 2 episodes
• Robustness — 5× in this paper · explained in 5 episodes
• Transformer — 5× in this paper · explained in 2 episodes
• Redundancy — 4× in this paper · explained in 2 episodes
• Conference on Computer Vision and Pattern Recognition — 3× in this paper
• Core — 3× in this paper · explained in 2 episodes
• Finite Scalar Quantization — 3× in this paper
• Residual Vector Quantization — 3× in this paper
• AUC — 2× in this paper · explained in 2 episodes
• Embeddings — 2× in this paper · explained in 2 episodes
• Fidelity — 2× in this paper · explained in 2 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• IEEE International Conference on Robotics and Automation — 2× in this paper
• Representation Learning — 2× in this paper · explained in 2 episodes
• Tokenization — 2× in this paper · explained in 2 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Ablation study — 1× in this paper · explained in 1 episode
• Adaptability — 1× in this paper · explained in 1 episode
• Allocator — 1× in this paper · explained in 1 episode
• Clustering — 1× in this paper · explained in 2 episodes
• Communication Overhead — 1× in this paper · explained in 2 episodes
• Decode — 1× in this paper · explained in 2 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• In CVF International Conference on Computer Vision — 1× in this paper
• In International Conference on Learning Representations — 1× in this paper
• Latent Space — 1× in this paper · explained in 7 episodes
• Multi-Agent System — 1× in this paper · explained in 6 episodes
• Point Clouds — 1× in this paper · explained in 2 episodes
• Sparse Attention — 1× in this paper · explained in 5 episodes
• Sparsity — 1× in this paper · explained in 4 episodes
• Vector Quantization (VQ) — 1× in this paper · explained in 2 episodes
• Winter Conference on Applications of Computer Vision — 1× in this paper

Sources

• Pragmatic Communication in Multi-Agent Collaborative Perception
• Residual Vector Quantization For Communication-Efficient Multi-Agent Perception
• JigsawComm: Joint Semantic Feature Encoding and Transmission for Communication-Efficient Cooperative Perception
• InfoCom: Kilobyte-Scale Communication-Efficient Collaborative Perception with Information Bottleneck
• mmCooper: A Multi-agent Multi-stage Communication-efficient and Collaboration-robust Cooperative Perception Framework
• Rate-Distortion Optimized Communication for Collaborative Perception
• Finite Scalar Quantization: VQ-VAE Made Simple
• Theory and Experiments on Vector Quantized Autoencoders
• QuantV2X: A Fully Quantized Multi-Agent System for Cooperative Perception
• CoBEVT: Cooperative Bird's Eye View Semantic Segmentation with Sparse Transformers

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