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20182024
most citedLane-Change in Dense Traffic with Model Predictive Control and Neural Networks

34 citations · 41 across the 7 of their papers we have counts for

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16 papers · 1 filter

cs.CV2023

Uncovering the Missing Pattern: Unified Framework Towards Trajectory Imputation and Prediction

Yi Xu, Armin Bazarjani, Hyung-gun Chi +2

Trajectory prediction is a crucial undertaking in understanding entity movement or human behavior from observed sequences. However, current methods often assume that the observed s…

cs.CV2022★ 2 cited

DRAMA: Joint Risk Localization and Captioning in Driving

Srikanth Malla, Chiho Choi, Isht Dwivedi +2

Considering the functionality of situational awareness in safety-critical automation systems, the perception of risk in driving scenes and its explainability is of particular impor…

cs.CV2022★ 1 cited

Weakly-Supervised Online Action Segmentation in Multi-View Instructional Videos

Reza Ghoddoosian, Isht Dwivedi, Nakul Agarwal +2

This paper addresses a new problem of weakly-supervised online action segmentation in instructional videos. We present a framework to segment streaming videos online at test time u…

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

LOKI: Long Term and Key Intentions for Trajectory Prediction

Harshayu Girase, Haiming Gang, Srikanth Malla +4

Recent advances in trajectory prediction have shown that explicit reasoning about agents' intent is important to accurately forecast their motion. However, the current research act…

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…