Long-SCOPE: Fully Sparse Long-Range Cooperative 3D Perception

• URL: http://arxiv.org/abs/2604.09206v1
• Date: Fri, 10 Apr 2026 10:47:49 GMT
• Title: Long-SCOPE: Fully Sparse Long-Range Cooperative 3D Perception
• Abstract summary: Long-SCOPE is a fully sparse framework designed for robust long-distance cooperative 3D perception.<n>Our method features two novel components: a Geometry-guided Query Generation module to accurately detect small, distant objects, and a learnable Context-Aware Association module that robustly matches cooperative queries.<n>Experiments on the V2X-Seq and Griffin datasets validate that Long-SCOPE achieves state-of-the-art performance, particularly in challenging 100-150 m long-range settings.
• Score: 22.880970790986357
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Cooperative 3D perception via Vehicle-to-Everything communication is a promising paradigm for enhancing autonomous driving, offering extended sensing horizons and occlusion resolution. However, the practical deployment of existing methods is hindered at long distances by two critical bottlenecks: the quadratic computational scaling of dense BEV representations and the fragility of feature association mechanisms under significant observation and alignment errors. To overcome these limitations, we introduce Long-SCOPE, a fully sparse framework designed for robust long-distance cooperative 3D perception. Our method features two novel components: a Geometry-guided Query Generation module to accurately detect small, distant objects, and a learnable Context-Aware Association module that robustly matches cooperative queries despite severe positional noise. Experiments on the V2X-Seq and Griffin datasets validate that Long-SCOPE achieves state-of-the-art performance, particularly in challenging 100-150 m long-range settings, while maintaining highly competitive computation and communication costs.

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