Training scene flow networks on 940k synthetic CARLA LiDAR frames transfers zero-shot to real benchmarks and makes 5% real labels beat 20%.
arXiv preprint arXiv:2311.15615 (2023)
2 Pith papers cite this work. Polarity classification is still indexing.
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AutoMine applies LLMs and VLMs with self-refining code generation to scenario mining and reports 36.38 HOTA-Temporal and 77.21 Timestamp BA on the AV2 2026 challenge.
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SynFlow: Scaling Up LiDAR Scene Flow Estimation with Synthetic Data
Training scene flow networks on 940k synthetic CARLA LiDAR frames transfers zero-shot to real benchmarks and makes 5% real labels beat 20%.
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AutoMine Solution for AV2 2026 Scenario Mining Challenge
AutoMine applies LLMs and VLMs with self-refining code generation to scenario mining and reports 36.38 HOTA-Temporal and 77.21 Timestamp BA on the AV2 2026 challenge.