9 citations · 14 across the 6 of their papers we have counts for
6 papers
Pedestrian Trajectory Prediction with Missing Data: Datasets, Imputation, and Benchmarking
Pranav Singh Chib, Pravendra Singh
Pedestrian trajectory prediction is crucial for several applications such as robotics and self-driving vehicles. Significant progress has been made in the past decade thanks to the…
CCF: Cross Correcting Framework for Pedestrian Trajectory Prediction
Pranav Singh Chib, Pravendra Singh
Accurately predicting future pedestrian trajectories is crucial across various domains. Due to the uncertainty in future pedestrian trajectories, it is important to learn complex s…
LG-Traj: LLM Guided Pedestrian Trajectory Prediction
Pranav Singh Chib, Pravendra Singh
Accurate pedestrian trajectory prediction is crucial for various applications, and it requires a deep understanding of pedestrian motion patterns in dynamic environments. However,…
Enhancing Trajectory Prediction through Self-Supervised Waypoint Noise Prediction
Pranav Singh Chib, Pravendra Singh
Trajectory prediction is an important task that involves modeling the indeterminate nature of traffic actors to forecast future trajectories given the observed trajectory sequences…
Improving Trajectory Prediction in Dynamic Multi-Agent Environment by Dropping Waypoints
Pranav Singh Chib, Pravendra Singh
The inherently diverse and uncertain nature of trajectories presents a formidable challenge in accurately modeling them. Motion prediction systems must effectively learn spatial an…
Recent Advancements in End-to-End Autonomous Driving using Deep Learning: A Survey
Pranav Singh Chib, Pravendra Singh
End-to-End driving is a promising paradigm as it circumvents the drawbacks associated with modular systems, such as their overwhelming complexity and propensity for error propagati…