Human Trajectory Prediction

Latest papers

14 papers1 paper in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

Revisiting Numerical Forecasting Models for Language-Based Trajectory Prediction
Oct 6, 2026JunGyu Lee, Inhwan Bae, Hae-Gon JeonReward Modeling RL for Language Models
Yonsei University · DGIST
GEAR: From Dynamic Encoding to Dynamic Activation in Social Trajectory Prediction
Sep 12, 2026Jiaheng Chen, Jiaxing Li, Leixia Wang +2Human Trajectory Prediction Pedestrian Trajectory Prediction
Software College Northeastern University Shenyang, China
Congestion-Aware Robot Tour Planning in Crowded Environments
Jun 17, 2026Stefano Bernagozzi, Charlie Street, Masoumeh Mansouri +1Robot Navigation Human Trajectory Prediction
1Istituto Italiano di Tecnologia – Genova, Italia · 2Universit`a di Genova – Genova, Italia · University of Birmingham – Birmingham, United Kingdom
An Attention-based Model for Robust Forecasting with Missing Modality
Jun 11, 2026Zhitian Zhang, Wenjie Zi, Yunduz Rakhmangulova +3Missing-Modality Learning Human Trajectory Prediction
1Simon Fraser University · 2RBC Borealis
HCSG: Human-Centric Semantic-Geometric Reasoning for Vision-Language Navigation
May 13, 2026Haoxuan Xu, Tianfu Li, Wenbo Chen +7Social Robot Navigation Vision-Language Navigation
The Hong Kong University of Science and Technology (Guangzhou), Guangzhou 511453, China · Tsinghua University, Shenzhen 518055, China · University of Science and Technology Beijing, Beijing 100083, China +2
JACoP: Joint Alignment for Compliant Multi-Agent Prediction
May 12, 2026Qingze Liu, Alen Mrdovic, Danrui Li +3Pedestrian Trajectory Prediction Markov Random Fields
Rutgers University, New Brunswick · The College of New Jersey
Chatting about Conditional Trajectory Prediction
Apr 20, 2026Yuxiang Zhao, Wei Huang, Haipeng Zeng +2Multi-Agent Trajectory Prediction Human Behavior Prediction
Sun Yat-sen University · Alibaba Group
TrajMamba: An Ego-Motion-Guided Mamba Model for Pedestrian Trajectory Prediction from an Egocentric Perspective
Mar 16, 2026Yusheng Peng, Gaofeng Zhang, Liping ZhengPedestrian Trajectory Prediction Trajectory Prediction
School of Computer Science and Information Engineering, Hefei University of Technology, Hefei 230601, China · School of Software, Hefei University of Technology, Hefei 230601, China
AutoTraces: Autoregressive Trajectory Forecasting via Multimodal Large Language Models
Mar 9, 2026Teng Wang, Yanting Lu, Ruize WangRobot Motion Prediction Trajectory Prediction
SimpliHuMoN: Simplifying Human Motion Prediction
Mar 4, 2026Aadya Agrawal, Alexander SchwingHuman Motion Prediction Human Trajectory Prediction
University of Illinois Urbana-Champaign, USA
Robust Human Trajectory Prediction via Self-Supervised Skeleton Representation Learning
Feb 26, 2026Taishu Arashima, Hiroshi Kera, Kazuhiko KawamotoHuman Trajectory Prediction Trajectory Prediction
Chiba University
EgoCogNav: Cognition-aware Human Egocentric Navigation
Nov 15, 2025Zhiwen Qiu, Ziang Liu, Wenqian Niu +2Robot Navigation Egocentric Video Understanding
Cornell University, Ithaca, NY, USA · Georgia Institute of Technology, Atlanta, GA, USA
NeMo-map: Neural Implicit Flow Fields for Spatio-Temporal Motion Mapping
Oct 16, 2025Yufei Zhu, Shih-Min Yang, Andrey Rudenko +3Implicit Neural Representations Human Trajectory Prediction
Orebro University, Sweden · Technical University of Munich, Germany · Aalto University, Finland
User Trajectory Prediction Unifying Global and Local Temporal Information
Aug 4, 2025Wei Hao, Bin Chong, Ronghua Ji +1Human Trajectory Prediction Trajectory Prediction
College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China · National Engineering Laboratory for Big Data Analysis and Applications, Peking University, Beijing 100871, China

Oct 6, 2026J/K move · Enter open · S save

Revisiting Numerical Forecasting Models for Language-Based Trajectory Prediction

JunGyu Lee, Inhwan Bae, Hae-Gon Jeon

Yonsei University · DGIST

Reward Modeling RL for Language Models Trajectory Generation Pedestrian Trajectory Prediction Trajectory Prediction Human Trajectory Prediction

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Language-based trajectory predictors represent coordinates as discrete tokens and learn auxiliary tasks such as destination and group reasoning. This formulation enables the model to capture behavioral intent and social context beyond coordinate dynamics alone. However, token-level objectives provide only indirect guidance for continuous coordinate-space dynamics. To address this limitation, we introduce MoRE (Mixture of Reward Experts), a refinement framework that transfers numerical forecasting priors into a pretrained language-based predictor through reinforcement learning. Five frozen numerical predictors provide complementary coordinate-level knowledge of motion and interactions. Their predictions are converted into expert rewards and combined through an uncertainty-weighted consensus that penalizes disagreement. A ground-truth reward anchors the prediction to the target trajectory. To focus refinement on difficult cases, MoRE refines the policy using the top 1% of training samples ranked by predictive entropy. Expert predictions are computed once and cached before PPO training, so the experts are not run during policy updates or inference. In this way, MoRE combines the contextual modeling of the language-based predictor with coordinate-level feedback from numerical experts. On ETH-UCY, MoRE reduces ADE from 0.22 to 0.20 m and FDE from 0.32 to 0.29 m. Relative to the base policy, ADE decreases by 17.9% on SDD and 12.7% on NBA. On ETH-UCY, MoRE also reduces collision rates and better matches ground-truth pedestrian spacing, without increasing measured inference memory or latency. The project page is available at https://jungyu0413.github.io/MoRE/.