Multi-Agent Trajectory Prediction

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6 papers in the last four weeks, with none the four weeks before. 0.1% of all new papers.

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A Pedestrian-Vehicle Interaction Benchmark and Annotation Framework for Unstructured Scenes via Uncalibrated Cameras
May 25, 2026Haoyang Peng, Qian Hu, Songan Zhang +1Autonomous Driving Datasets Autonomous Driving Benchmarks
School of Automation and Intelligent Sensing, Shanghai Jiao Tong University, Shanghai 200240, China · Global Institute of Future Technology, Shanghai Jiao Tong University, Shanghai 200240, China
Agent-Centric Social Trajectory Prediction: A Free Energy Principle Perspective
May 25, 2026Yanping Wu, Ji Zhang, Hao Chen +2Multi-Agent Trajectory Prediction Probabilistic Forecasting
University of Glasgow Glasgow, UK · Southwest Jiaotong University Chengdu, China
Diverse Yet Consistent: Context-Guided Diffusion with Energy-Based Joint Refinement for Multi-Agent Motion Prediction
May 21, 2026Lei Chu, Yuhuan ZhaoMulti-Agent Trajectory Prediction Human Motion Generation
University of Southern California, Los Angeles, CA, USA
On Improving Multimodal Pedestrian Trajectory Prediction with CVAE: A Study on Benchmark and Robot Data
May 18, 2026Yuzhou Liu, Cristina Olaverri-MonrealPedestrian Behavior Modeling Pedestrian Trajectory Prediction
Dept. Intelligent Transport Systems, Johannes Kepler University Linz, Altenberger Straße 69, 4040 Linz, Austria.
Social-Mamba: Socially-Aware Trajectory Forecasting with State-Space Models
May 14, 2026Po-Chien Luan, Wuyang Li, Yang Gao +1Pedestrian Behavior Modeling Pedestrian Trajectory Prediction
EPFL, Switzerland
Exploitation of Hidden Context in Dynamic Movement Forecasting: A Neural Network Journey from Recurrent to Graph Neural Networks and General Purpose Transformers
May 14, 2026Lukas Schelenz, Shobha Rajanna, Denis Gosalci +6Graph Neural Networks Multi-Agent Trajectory Prediction
Fraunhofer Institute for Integrated Circuits IIS, 90411 Nürnberg, Germany · Friedrich-Alexander-Universität Erlangen-Nürnberg, 91058 Erlangen, Germany
Causality-Aware End-to-End Autonomous Driving via Ego-Centric Joint Scene Modeling
May 13, 2026Seokha Moon, Minseung Lee, Joon Seo +2Causal Representation Learning End-to-End Autonomous Driving
Korea University · Kakao Mobility
Encore: Conditioning Trajectory Forecasting via Biased Ego Rehearsals
May 12, 2026Conghao Wong, Ziqian Zou, Xinge YouMulti-Agent Trajectory Prediction Trajectory Prediction
Huazhong University of Science and Technology, Wuhan 430074, Hubei, China.
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
Heteroscedastic Diffusion for Multi-Agent Trajectory Modeling
May 11, 2026Guillem Capellera, Antonio Rubio, Luis Ferraz +1Multi-Agent Trajectory Prediction Trajectory Prediction
Institut de Rob`otica i Inform`atica Industrial, CSIC-UPC, Barcelona, 08028, Spain · Kognia Sports Intelligence, 08960, Sant Just Desvern, Spain
ECTraj: Enhanced Consistency Training for Multi-Agent Trajectory Prediction
May 9, 2026Alen Mrdovic, Qingze, Liu +6Trajectory Generation Multi-Agent Trajectory Prediction
Tony · Rutgers University, New Brunswick · The College of New Jersey
Recall to Predict: Grounding Motion Forecasting in Interpretable Motion Bank
May 2, 2026Abhishek Vivekanandan, Ahmed Abouelazm, J. Marius ZöllnerMulti-Agent Trajectory Prediction Multimodal Trajectory Prediction
FZI Forschungszentrum Informatik · Karlsruhe Institute of Technology (KIT) Karlsruhe, Germany
FlowS: One-Step Motion Prediction via Local Transport Conditioning
Apr 28, 2026Leandro Di Bella, Adrian Munteanu, Bruno CornelisFlow Matching Trajectory Generation
Department of Electronics and Informatics, Vrije Universiteit Brussel, Pleinlaan 2, B-1050 Brussels, Belgium · IMEC, Kapeldreef 75, B-3001 Leuven, Belgium
SceneSelect: Selective Learning for Trajectory Scene Classification and Expert Scheduling
Apr 27, 2026Xinrun Wang, Deshun Xia, Yuxi Sun +1Multi-Agent Trajectory Prediction Expert Routing
School of Computer Science, China University of Geosciences (Wuhan) · School of Information Engineering, Wuhan University of Technology · School of Mathematics and Statistics, Wuhan University of Technology
Collaborative Trajectory Prediction via Late Fusion
Apr 24, 2026Nadya Abdel Madjid, Murad Mebrahtu, Zakhar Yagudin +5Multi-Agent Trajectory Prediction V2X Communication
Khalifa University, Computer Science, Abu Dhabi, UAE · Khalifa University, KUCARS-KU Center for Autonomous Robotic Systems, Department of Computer Science, Abu Dhabi, UAE · Khalifa University, Computer and Information Engineering, Abu Dhabi, UAE +2
Frozen LLMs as Map-Aware Spatio-Temporal Reasoners for Vehicle Trajectory Prediction
Apr 23, 2026Yanjiao Liu, Jiawei Liu, Xun Gong +1Multi-Agent Trajectory Prediction Autonomous Driving
School of Artificial Intelligence, Jilin University, Changchun 130012, PR China.
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
EdgeVTP: Exploration of Latency-efficient Trajectory Prediction for Edge-based Embedded Vision Applications
Apr 18, 2026Seungjin Kim, Reza Jafarpourmarzouni, Christopher Neff +2Efficient Neural Network Inference Edge Inference
University of Wyoming · University of North Carolina at Charlotte · North Carolina A&T State University
MAVEN-T: Reinforced Heterogeneous Distillation for Real-Time Multi-Agent Trajectory Prediction
Apr 11, 2026Wenchang Duan, Zhenguo Gao, Jinguo Xian +1Model Compression Multi-Agent Trajectory Prediction
School of Mathematical Sciences, Shanghai Jiao Tong University, Shanghai 200240, China · Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Shanghai Jiao Tong University, Shanghai 200030, China · Shanghai Key Laboratory of Psychotic Disorders, and Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai 200030, China
Reverberation: Learning the Latencies Before Forecasting Trajectories
Nov 14, 2025Conghao Wong, Ziqian Zou, Beihao Xia +1Multi-Agent Trajectory Prediction Agent Trajectory Analysis
Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
Hi-FLoop: Hierarchical State-Feedback Loops for Multi-Timescale World Modeling
Date pendingRx Fan, Z HanMulti-Agent Trajectory Prediction Multimodal Trajectory Prediction
School of Systems Science, Beijing Normal University

May 25, 2026, cs.CVJ/K move · Enter open · S save

A Pedestrian-Vehicle Interaction Benchmark and Annotation Framework for Unstructured Scenes via Uncalibrated Cameras

Haoyang Peng, Qian Hu, Songan Zhang, Ming Yang

School of Automation and Intelligent Sensing, Shanghai Jiao Tong University, Shanghai 200240, China · Global Institute of Future Technology, Shanghai Jiao Tong University, Shanghai 200240, China

Autonomous Driving Datasets Autonomous Driving Benchmarks Multi-Agent Trajectory Prediction Autonomous Driving Autonomous Driving Perception

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Predicting the interaction between pedestrian and vehicle is essential for autonomous driving safety in unstructured and semi-structured scenarios; however, this task is severely hindered by the scarcity of public datasets that feature dense pedestrian-vehicle interactions. Most current studies rely on structured road data, leaving the complex, heterogeneous interactions found in unstructured environments insufficiently represented and researched. In this paper, we propose a dataset annotation framework based on video data from uncalibrated surveillance cameras and present PINNS (Pedestrian-vehicle Interaction dataset from uNcalibrated cameras in uNstructured Scenes). The dataset covers multiple countries and regions, includes diverse typical traffic scenarios, and considers variations in seasons, lighting conditions, and weather. It focuses on complex scenes with dense pedestrian-vehicle interactions and is designed to be easily extensible. The dataset is constructed and annotated according to the standard issued by the Chinese Association of Automation, providing both trajectory data and corresponding scene-level information. Furthermore, this paper analyzes current challenges and research directions in heterogeneous agent trajectory prediction, shows the necessity and usefulness of the proposed dataset. We hope our framework and dataset will facilitate research on trajectory prediction and autonomous driving in complex mixed traffic scenarios. PINNS is publicly available at https://github.com/Songan-Lab.

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