Mode-as-Sequence turns unordered multimodal trajectory sets into ordered sequences with explicit mode dependencies via recurrent or parallel decoding plus EMTA loss, yielding top rankings on Waymo motion prediction challenges.
Large scale interactive motion forecasting for autonomous driving: The waymo open motion dataset
5 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 5representative citing papers
MISTY delivers state-of-the-art closed-loop scores on nuPlan Test14-hard (80.32 non-reactive, 82.21 reactive) at 10.1 ms latency via single-step MLP-Mixer inference and a latent drifting loss that encourages proactive maneuvers.
FlowS achieves state-of-the-art single-step motion prediction on Waymo Open Motion Dataset by using scene-conditioned anchor trajectories and a step-consistent displacement field to make local transport accurate in one Euler step.
A platform using flow matching for real-world image generation and an adversarial policy creates challenging corner cases to evaluate end-to-end autonomous driving models like UniAD and VAD, showing performance degradation.
VR study finds eye gaze adds complementary information to pedestrian trajectory prediction models, cutting final displacement error by 8.47% when fused with situational context.
citing papers explorer
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Mode-as-Sequence: Translating Multimodal Motion Prediction into Unified Sequential Mode Modeling
Mode-as-Sequence turns unordered multimodal trajectory sets into ordered sequences with explicit mode dependencies via recurrent or parallel decoding plus EMTA loss, yielding top rankings on Waymo motion prediction challenges.
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MISTY: High-Throughput Motion Planning via Mixer-based Single-step Drifting
MISTY delivers state-of-the-art closed-loop scores on nuPlan Test14-hard (80.32 non-reactive, 82.21 reactive) at 10.1 ms latency via single-step MLP-Mixer inference and a latent drifting loss that encourages proactive maneuvers.
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FlowS: One-Step Motion Prediction via Local Transport Conditioning
FlowS achieves state-of-the-art single-step motion prediction on Waymo Open Motion Dataset by using scene-conditioned anchor trajectories and a step-consistent displacement field to make local transport accurate in one Euler step.
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Driving in Corner Case: A Real-World Adversarial Closed-Loop Evaluation Platform for End-to-End Autonomous Driving
A platform using flow matching for real-world image generation and an adversarial policy creates challenging corner cases to evaluate end-to-end autonomous driving models like UniAD and VAD, showing performance degradation.
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Eye Gaze-Informed and Context-Aware Pedestrian Trajectory Prediction in Shared Spaces with Automated Shuttles: A Virtual Reality Study
VR study finds eye gaze adds complementary information to pedestrian trajectory prediction models, cutting final displacement error by 8.47% when fused with situational context.