activity
20182026
most citedSocial-WaGDAT: Interaction-aware Trajectory Prediction via Wasserstein Graph Double-Attention Network

51 citations · 114 across the 16 of their papers we have counts for

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Showing cs.CVShow all

7 papers · 1 filter

cs.CV2022★ 3 cited

EvolveHypergraph: Group-Aware Dynamic Relational Reasoning for Trajectory Prediction

Jiachen Li, Chuanbo Hua, Jinkyoo Park +3

While the modeling of pair-wise relations has been widely studied in multi-agent interacting systems, its ability to capture higher-level and larger-scale group-wise activities is…

cs.CV2022

Important Object Identification with Semi-Supervised Learning for Autonomous Driving

Jiachen Li, Haiming Gang, Hengbo Ma +2

Accurate identification of important objects in the scene is a prerequisite for safe and high-quality decision making and motion planning of intelligent agents (e.g., autonomous ve…

cs.CV2021★ 1 cited

RAIN: Reinforced Hybrid Attention Inference Network for Motion Forecasting

Jiachen Li, Fan Yang, Hengbo Ma +3

Motion forecasting plays a significant role in various domains (e.g., autonomous driving, human-robot interaction), which aims to predict future motion sequences given a set of his…

cs.CV2021★ 4 cited

Spectral Temporal Graph Neural Network for Trajectory Prediction

Defu Cao, Jiachen Li, Hengbo Ma +1

An effective understanding of the contextual environment and accurate motion forecasting of surrounding agents is crucial for the development of autonomous vehicles and social mobi…

cs.CV2021

Spatio-Temporal Graph Dual-Attention Network for Multi-Agent Prediction and Tracking

Jiachen Li, Hengbo Ma, Zhihao Zhang +2

An effective understanding of the environment and accurate trajectory prediction of surrounding dynamic obstacles are indispensable for intelligent mobile systems (e.g. autonomous…

cs.CV2020★ 51 cited

Social-WaGDAT: Interaction-aware Trajectory Prediction via Wasserstein Graph Double-Attention Network

Jiachen Li, Hengbo Ma, Zhihao Zhang +1

Effective understanding of the environment and accurate trajectory prediction of surrounding dynamic obstacles are indispensable for intelligent mobile systems (like autonomous veh…