C Jiang, A Cornman, C Park, B Sapp… - Proceedings of the …, 2023 - openaccess.thecvf.com
We present MotionDiffuser, a diffusion based representation for the joint distribution of future trajectories over multiple agents. Such representation has several key advantages: first, our …
C Xu, M Li, Z Ni, Y Zhang… - Proceedings of the IEEE …, 2022 - openaccess.thecvf.com
Demystifying the interactions among multiple agents from their past trajectories is fundamental to precise and interpretable trajectory prediction. However, previous works only …
C Xu, W Mao, W Zhang, S Chen - Proceedings of the IEEE …, 2022 - openaccess.thecvf.com
To realize trajectory prediction, most previous methods adopt the parameter-based approach, which encodes all the seen past-future instance pairs into model parameters …
Recent advances in trajectory prediction have shown that explicit reasoning about agents' intent is important to accurately forecast their motion. However, the current research …
E Sachdeva, N Agarwal, S Chundi… - Proceedings of the …, 2024 - openaccess.thecvf.com
The widespread adoption of commercial autonomous vehicles (AVs) and advanced driver assistance systems (ADAS) may largely depend on their acceptance by society, for which …
W Luo, C Park, A Cornman, B Sapp… - Conference on Robot …, 2023 - proceedings.mlr.press
Abstract We propose\textit {JFP}, a Joint Future Prediction model that can learn to generate accurate and consistent multi-agent future trajectories. For this task, many different methods …
Human motion prediction aims to forecast future poses given a sequence of past 3D skeletons. While this problem has recently received increasing attention, it has mostly been …
H Ma, J Li, R Hosseini… - Proceedings of the …, 2022 - openaccess.thecvf.com
Obtaining accurate and diverse human motion prediction is essential to many industrial applications, especially robotics and autonomous driving. Recent research has explored …
L Rowe, M Ethier, EH Dykhne… - Proceedings of the …, 2023 - openaccess.thecvf.com
Predicting the future motion of road agents is a critical task in an autonomous driving pipeline. In this work, we address the problem of generating a set of scene-level, or joint …