mlsanityData to 7 Oct 2026

Resonance: Learning to Predict Social-Aware Pedestrian Trajectories as Co-Vibrations

arXiv 2412.02447 ↗First posted 3 Dec 2024cs.CVcited by 5

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Abstract (arXiv)

Learning to forecast trajectories of intelligent agents has caught much more attention recently. However, it remains a challenge to accurately account for agents' intentions and social behaviors when forecasting, and in particular, to simulate the unique randomness within each of those components in an explainable and decoupled way. Inspired by vibration systems and their resonance properties, we propose the Resonance (short for Re) model to encode and forecast pedestrian trajectories in the form of ``co-vibrations''. It decomposes trajectory modifications and randomnesses into multiple vibration portions to simulate agents' reactions to each single cause, and forecasts trajectories as the superposition of these independent vibrations separately. Also, benefiting from such vibrations and their spectral properties, representations of social interactions can be learned by emulating the resonance phenomena, further enhancing its explainability. Experiments on multiple datasets have verified its usefulness both quantitatively and qualitatively.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 58 of its 98 references that are in the map. First posted on arXiv 3 Dec 2024.

Builds on

58 of 98 references.

References · 58

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38 more
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50 most cited of 58 All 58 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 2; 2026: 3.

5 papers.

  1. 2025Recent Advances in Multi-Agent Human Trajectory Prediction: A Comprehensive Reviewcited by 2
  2. 2025Reverberation: Learning the Latencies Before Forecasting Trajectoriescited by 1
  3. 2026Encore: Conditioning Trajectory Forecasting via Biased Ego Rehearsalscited by 0
  4. 2026A Unified Framework for Trajectory Prediction with Explicit Planning and Reaction Decompositioncited by 0
  5. 2026GEAR: From Dynamic Encoding to Dynamic Activation in Social Trajectory Predictioncited by 0