Publications (4)
TrajDiffuse: A Conditional Diffusion Model for Environment-Aware Trajectory Prediction
Qingze, Liu, Danrui Li +4
Accurate prediction of human or vehicle trajectories with good diversity that captures their stochastic nature is an essential task for many applications. However, many trajectory…
ECTraj: Enhanced Consistency Training for Multi-Agent Trajectory Prediction
Alen Mrdovic, Qingze, Liu +6
Diffusion models for multi-agent trajectory prediction are limited by iterative denoising, which causes inference latency that hinders their use in time-critical settings like auto…
Judging from Support-set: A New Way to Utilize Few-Shot Segmentation for Segmentation Refinement Process
Seonghyeon Moon, Qingze, Liu +2
Segmentation refinement aims to enhance the initial coarse masks generated by segmentation algorithms. The refined masks are expected to capture more details and better contours of…
Self Expanding Convolutional Neural Networks
Blaise Appolinary, Alex Deaconu, Sophia Yang +2
In this paper, we present a novel method for dynamically expanding Convolutional Neural Networks (CNNs) during training, aimed at meeting the increasing demand for efficient and su…