AI RESEARCH
SHARP: Short-Window Streaming for Accurate and Robust Prediction in Motion Forecasting
arXiv CS.CV
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ArXi:2603.28091v1 Announce Type: new In dynamic traffic environments, motion forecasting models must be able to accurately estimate future trajectories continuously. Streaming-based methods are a promising solution, but despite recent advances, their performance often degrades when exposed to heterogeneous observation lengths. To address this, we propose a novel streaming-based motion forecasting framework that explicitly focuses on evolving scenes.