Search Results for author:
Found 11 papers, 1 papers with code
TSGN: Temporal Scene Graph Neural Networks with Projected Vectorized Representation for Multi-Agent Motion Prediction
Meanwhile, we propose a Hierarchical Lane Transformer for capturing interactions between agents and road network, which filters the surrounding road network and only keeps the most probable lane segments which could have an impact on the future behavior of the target agent.
CROSSFIRE: Camera Relocalization On Self-Supervised Features from an Implicit Representation
Beyond novel view synthesis, Neural Radiance Fields are useful for applications that interact with the real world.
Uncertainty estimation for Cross-dataset performance in Trajectory prediction
While a lot of work has been carried on developing trajectory prediction methods, and various datasets have been proposed for benchmarking this task, little study has been done so far on the generalizability and the transferability of these methods across dataset.
ImPosing: Implicit Pose Encoding for Efficient Visual Localization
We propose a novel learning-based formulation for visual localization of vehicles that can operate in real-time in city-scale environments.
Assessing Cross-dataset Generalization of Pedestrian Crossing Predictors
Pedestrian crossing prediction has been a topic of active research, resulting in many new algorithmic solutions.
LENS: Localization enhanced by NeRF synthesis
Neural Radiance Fields (NeRF) have recently demonstrated photo-realistic results for the task of novel view synthesis.
THOMAS: Trajectory Heatmap Output with learned Multi-Agent Sampling
In this paper, we propose THOMAS, a joint multi-agent trajectory prediction framework allowing for an efficient and consistent prediction of multi-agent multi-modal trajectories.
Ranked #6 on
Trajectory Prediction
on nuScenes
GOHOME: Graph-Oriented Heatmap Output for future Motion Estimation
In this paper, we propose GOHOME, a method leveraging graph representations of the High Definition Map and sparse projections to generate a heatmap output representing the future position probability distribution for a given agent in a traffic scene.
Ranked #1 on
Trajectory Prediction
on INTERACTION Dataset - Validation
(minFDE6 metric)
TrouSPI-Net: Spatio-temporal attention on parallel atrous convolutions and U-GRUs for skeletal pedestrian crossing prediction
In this paper, we address pedestrian crossing prediction in urban traffic environments by linking the dynamics of a pedestrian's skeleton to a binary crossing intention.
HOME: Heatmap Output for future Motion Estimation
In this paper, we propose HOME, a framework tackling the motion forecasting problem with an image output representing the probability distribution of the agent's future location.
Ranked #32 on
Motion Forecasting
on Argoverse CVPR 2020
CoordiNet: uncertainty-aware pose regressor for reliable vehicle localization
In this setup, structure-based methods require a large database, and we show that our proposal is a reliable alternative, achieving 29cm median error in a 1. 9km loop in a busy urban area
Ranked #2 on
Camera Localization
on Oxford RobotCar Full
