41 citations · 73 across the 27 of their papers we have counts for
5 papers · 2 filters
PPT: Pretraining with Pseudo-Labeled Trajectories for Motion Forecasting
Yihong Xu, Yuan Yin, Éloi Zablocki +3
Accurately predicting how agents move in dynamic scenes is essential for safe autonomous driving. State-of-the-art motion forecasting models rely on datasets with manually annotate…
GIFT: A Framework Towards Global Interpretable Faithful Textual Explanations of Vision Classifiers
Éloi Zablocki, Valentin Gerard, Amaia Cardiel +3
Understanding the decision processes of deep vision models is essential for their safe and trustworthy deployment in real-world settings. Existing explainability approaches, such a…
LLM-wrapper: Black-Box Semantic-Aware Adaptation of Vision-Language Models for Referring Expression Comprehension
Amaia Cardiel, Eloi Zablocki, Elias Ramzi +2
Vision Language Models (VLMs) have demonstrated remarkable capabilities in various open-vocabulary tasks, yet their zero-shot performance lags behind task-specific fine-tuned model…
Valeo4Cast: A Modular Approach to End-to-End Forecasting
Yihong Xu, Éloi Zablocki, Alexandre Boulch +11
Motion forecasting is crucial in autonomous driving systems to anticipate the future trajectories of surrounding agents such as pedestrians, vehicles, and traffic signals. In end-t…
UniTraj: A Unified Framework for Scalable Vehicle Trajectory Prediction
Lan Feng, Mohammadhossein Bahari, Kaouther Messaoud Ben Amor +3
Vehicle trajectory prediction has increasingly relied on data-driven solutions, but their ability to scale to different data domains and the impact of larger dataset sizes on their…