Progressively generating better initial guesses towards next stages for high-quality human motion prediction
This paper presents a high-quality human motion prediction method that accurately predicts
future human poses given observed ones. Our method is based on the observation that a …
future human poses given observed ones. Our method is based on the observation that a …
Trajectory unified transformer for pedestrian trajectory prediction
Pedestrian trajectory prediction is an essentially connecting link to understanding human
behavior. Recent works achieve state-of-the-art performance gained from the hand …
behavior. Recent works achieve state-of-the-art performance gained from the hand …
Eigentrajectory: Low-rank descriptors for multi-modal trajectory forecasting
Capturing high-dimensional social interactions and feasible futures is essential for
predicting trajectories. To address this complex nature, several attempts have been devoted …
predicting trajectories. To address this complex nature, several attempts have been devoted …
Sparse instance conditioned multimodal trajectory prediction
Pedestrian trajectory prediction is critical in many vision tasks but challenging due to the
multimodality of the future trajectory. Most existing methods predict multimodal trajectories …
multimodality of the future trajectory. Most existing methods predict multimodal trajectories …
Multi-stream representation learning for pedestrian trajectory prediction
Forecasting the future trajectory of pedestrians is an important task in computer vision with a
range of applications, from security cameras to autonomous driving. It is very challenging …
range of applications, from security cameras to autonomous driving. It is very challenging …
A set of control points conditioned pedestrian trajectory prediction
Predicting the trajectories of pedestrians in crowded conditions is an important task for
applications like autonomous navigation systems. Previous studies have tackled this …
applications like autonomous navigation systems. Previous studies have tackled this …
Social-ssl: Self-supervised cross-sequence representation learning based on transformers for multi-agent trajectory prediction
Earlier trajectory prediction approaches focus on ways of capturing sequential structures
among pedestrians by using recurrent networks, which is known to have some limitations in …
among pedestrians by using recurrent networks, which is known to have some limitations in …
Multimodal trajectory prediction: A survey
Trajectory prediction is an important task to support safe and intelligent behaviours in
autonomous systems. Many advanced approaches have been proposed over the years with …
autonomous systems. Many advanced approaches have been proposed over the years with …
Can Language Beat Numerical Regression? Language-Based Multimodal Trajectory Prediction
Abstract Language models have demonstrated impressive ability in context understanding
and generative performance. Inspired by the recent success of language foundation models …
and generative performance. Inspired by the recent success of language foundation models …
STGlow: A flow-based generative framework with dual-graphormer for pedestrian trajectory prediction
The pedestrian trajectory prediction task is an essential component of intelligent systems. Its
applications include but are not limited to autonomous driving, robot navigation, and …
applications include but are not limited to autonomous driving, robot navigation, and …