2 citations · 12 across the 21 of their papers we have counts for
23 papers
Stable Video Infinity: Infinite-Length Video Generation with Error Recycling
Wuyang Li, Wentao Pan, Po-Chien Luan +2
We propose Stable Video Infinity (SVI) that is able to generate infinite-length videos with high temporal consistency, plausible scene transitions, and controllable streaming story…
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…
Probabilistic Collision Risk Estimation for Pedestrian Navigation
Amine Tourki, Paul Prevel, Nils Einecke +2
Intelligent devices for supporting persons with vision impairment are becoming more widespread, but they are lacking behind the advancements in intelligent driver assistant system.…
From Generation to Generalization: Emergent Few-Shot Learning in Video Diffusion Models
Pablo Acuaviva, Aram Davtyan, Mariam Hassan +4
Video Diffusion Models (VDMs) have emerged as powerful generative tools, capable of synthesizing high-quality spatiotemporal content. Yet, their potential goes far beyond mere vide…
VoxDet: Rethinking 3D Semantic Occupancy Prediction as Dense Object Detection
Wuyang Li, Zhu Yu, Alexandre Alahi
3D semantic occupancy prediction aims to reconstruct the 3D geometry and semantics of the surrounding environment. With dense voxel labels, prior works typically formulate it as a…
EvoLM: In Search of Lost Language Model Training Dynamics
Zhenting Qi, Fan Nie, Alexandre Alahi +6
Modern language model (LM) training has been divided into multiple stages, making it difficult for downstream developers to evaluate the impact of design choices made at each stage…
X-GRM: Large Gaussian Reconstruction Model for Sparse-view X-rays to Computed Tomography
Yifan Liu, Wuyang Li, Weihao Yu +4
Computed Tomography serves as an indispensable tool in clinical workflows, providing non-invasive visualization of internal anatomical structures. Existing CT reconstruction works…
Weak-for-Strong: Training Weak Meta-Agent to Harness Strong Executors
Fan Nie, Lan Feng, Haotian Ye +5
Efficiently leveraging of the capabilities of contemporary large language models (LLMs) is increasingly challenging, particularly when direct fine-tuning is expensive and often imp…
COARSE: Collaborative Pseudo-Labeling with Coarse Real Labels for Off-Road Semantic Segmentation
Aurelio Noca, Xianmei Lei, Jonathan Becktor +6
Autonomous off-road navigation faces challenges due to diverse, unstructured environments, requiring robust perception with both geometric and semantic understanding. However, scar…
Unified Human Localization and Trajectory Prediction with Monocular Vision
Po-Chien Luan, Yang Gao, Celine Demonsant +1
Conventional human trajectory prediction models rely on clean curated data, requiring specialized equipment or manual labeling, which is often impractical for robotic applications.…
GEM: A Generalizable Ego-Vision Multimodal World Model for Fine-Grained Ego-Motion, Object Dynamics, and Scene Composition Control
Mariam Hassan, Sebastian Stapf, Ahmad Rahimi +17
We present GEM, a Generalizable Ego-vision Multimodal world model that predicts future frames using a reference frame, sparse features, human poses, and ego-trajectories. Hence, ou…
TAROT: Targeted Data Selection via Optimal Transport
Lan Feng, Fan Nie, Yuejiang Liu +1
We propose TAROT, a targeted data selection framework grounded in optimal transport theory. Previous targeted data selection methods primarily rely on influence-based greedy heuris…
A Multi-Loss Strategy for Vehicle Trajectory Prediction: Combining Off-Road, Diversity, and Directional Consistency Losses
Ahmad Rahimi, Alexandre Alahi
Trajectory prediction is essential for the safety and efficiency of planning in autonomous vehicles. However, current models often fail to fully capture complex traffic rules and t…
Multi-Transmotion: Pre-trained Model for Human Motion Prediction
Yang Gao, Po-Chien Luan, Alexandre Alahi
The ability of intelligent systems to predict human behaviors is crucial, particularly in fields such as autonomous vehicle navigation and social robotics. However, the complexity…
Strada-LLM: Graph LLM for traffic prediction
Seyed Mohamad Moghadas, Bruno Cornelis, Alexandre Alahi +1
Traffic forecasting is pivotal for intelligent transportation systems, where accurate and interpretable predictions can significantly enhance operational efficiency and safety. A k…
HEADS-UP: Head-Mounted Egocentric Dataset for Trajectory Prediction in Blind Assistance Systems
Yasaman Haghighi, Celine Demonsant, Panagiotis Chalimourdas +6
In this paper, we introduce HEADS-UP, the first egocentric dataset collected from head-mounted cameras, designed specifically for trajectory prediction in blind assistance systems.…
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-…
Certified Human Trajectory Prediction
Mohammadhossein Bahari, Saeed Saadatnejad, Amirhossein Askari Farsangi +2
Predicting human trajectories is essential for the safe operation of autonomous vehicles, yet current data-driven models often lack robustness in case of noisy inputs such as adver…
Co-Supervised Learning: Improving Weak-to-Strong Generalization with Hierarchical Mixture of Experts
Yuejiang Liu, Alexandre Alahi
Steering the behavior of a strong model pre-trained on internet-scale data can be difficult due to the scarcity of competent supervisors. Recent studies reveal that, despite superv…
Images in Discrete Choice Modeling: Addressing Data Isomorphism in Multi-Modality Inputs
Brian Sifringer, Alexandre Alahi
This paper explores the intersection of Discrete Choice Modeling (DCM) and machine learning, focusing on the integration of image data into DCM's utility functions and its impact o…
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…
Sim-to-Real Causal Transfer: A Metric Learning Approach to Causally-Aware Interaction Representations
Ahmad Rahimi, Po-Chien Luan, Yuejiang Liu +2
Modeling spatial-temporal interactions among neighboring agents is at the heart of multi-agent problems such as motion forecasting and crowd navigation. Despite notable progress, i…
JRDB-Traj: A Dataset and Benchmark for Trajectory Forecasting in Crowds
Saeed Saadatnejad, Yang Gao, Hamid Rezatofighi +1
Predicting future trajectories is critical in autonomous navigation, especially in preventing accidents involving humans, where a predictive agent's ability to anticipate in advanc…