2 citations · 7 across the 6 of their papers we have counts for
6 papers · 1 filter
Proprio: Latent Self-Scoring and Inference-Time Refinement for Physically Plausible Video Generation
Mariam Hassan, Kaouther Messaoud, Wuyang Li +1
Modern video generative models produce visually impressive results, yet frequently violate basic physical principles. We propose Proprio, a training-free framework that enables a f…
OmniTraj: Pre-Training on Heterogeneous Data for Adaptive and Zero-Shot Human Trajectory Prediction
Yang Gao, Po-Chien Luan, Kaouther Messaoud +2
While large-scale pre-training has advanced human trajectory prediction, a critical challenge remains: zero-shot transfer to unseen dataset with varying temporal dynamics. State-of…
Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting
Kaouther Messaoud, Matthieu Cord, Alexandre Alahi
Existing vehicle trajectory prediction models struggle with generalizability, prediction uncertainties, and handling complex interactions. It is often due to limitations like compl…
Forecast-PEFT: Parameter-Efficient Fine-Tuning for Pre-trained Motion Forecasting Models
Jifeng Wang, Kaouther Messaoud, Yuejiang Liu +2
Recent advancements in motion forecasting have been significantly accelerated by self-supervised pre-training techniques. However, current methods typically rely on extensive fine-…
Social-Transmotion: Promptable Human Trajectory Prediction
Saeed Saadatnejad, Yang Gao, Kaouther Messaoud +1
Accurate human trajectory prediction is crucial for applications such as autonomous vehicles, robotics, and surveillance systems. Yet, existing models often fail to fully leverage…
Trajectory Prediction for Autonomous Driving based on Multi-Head Attention with Joint Agent-Map Representation
Kaouther Messaoud, Nachiket Deo, Mohan M. Trivedi +1
Predicting the trajectories of surrounding agents is an essential ability for autonomous vehicles navigating through complex traffic scenes. The future trajectories of agents can b…