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Lehigh University, Bethlehem, PA, USA
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The LPCVC 2025 winning solutions showcase surprisingly effective strategies for balancing accuracy and efficiency in edge-based computer vision, pushing the boundaries of what's possible on resource-constrained devices.
Recommendation systems can now systematically debias engagement signals across user, content, and model dimensions using a lightweight, in-model approach, leading to more accurate value models and stable ecosystem dynamics.
Achieve temporally consistent HD maps by explicitly modeling historical map information and predicting short-term future motion of map instances.
