23 citations · 76 across the 8 of their papers we have counts for
9 papers
Valeo Near-Field: a novel dataset for pedestrian intent detection
Antonyo Musabini, Rachid Benmokhtar, Jagdish Bhanushali +3
This paper presents a novel dataset aimed at detecting pedestrians' intentions as they approach an ego-vehicle. The dataset comprises synchronized multi-modal data, including fishe…
Enhanced Parking Perception by Multi-Task Fisheye Cross-view Transformers
Antonyo Musabini, Ivan Novikov, Sana Soula +6
Current parking area perception algorithms primarily focus on detecting vacant slots within a limited range, relying on error-prone homographic projection for both labeling and inf…
Holistic Parking Slot Detection with Polygon-Shaped Representations
Lihao Wang, Antonyo Musabini, Christel Leonet +6
Current parking slot detection in advanced driver-assistance systems (ADAS) primarily relies on ultrasonic sensors. This method has several limitations such as the need to scan the…
VRUNet: Multi-Task Learning Model for Intent Prediction of Vulnerable Road Users
Adithya Ranga, Filippo Giruzzi, Jagdish Bhanushali +4
Advanced perception and path planning are at the core for any self-driving vehicle. Autonomous vehicles need to understand the scene and intentions of other road users for safe mot…
PLOP: Probabilistic poLynomial Objects trajectory Planning for autonomous driving
Thibault Buhet, Emilie Wirbel, Andrei Bursuc +1
To navigate safely in urban environments, an autonomous vehicle (ego vehicle) must understand and anticipate its surroundings, in particular the behavior and intents of other road…
Conditional Vehicle Trajectories Prediction in CARLA Urban Environment
Thibault Buhet, Emilie Wirbel, Xavier Perrotton
Imitation learning is becoming more and more successful for autonomous driving. End-to-end (raw signal to command) performs well on relatively simple tasks (lane keeping and naviga…
Imitation Learning for End to End Vehicle Longitudinal Control with Forward Camera
Laurent George, Thibault Buhet, Emilie Wirbel +2
In this paper we present a complete study of an end-to-end imitation learning system for speed control of a real car, based on a neural network with a Long Short Term Memory (LSTM)…
Sparse and Dense Data with CNNs: Depth Completion and Semantic Segmentation
Maximilian Jaritz, Raoul de Charette, Emilie Wirbel +2
Convolutional neural networks are designed for dense data, but vision data is often sparse (stereo depth, point clouds, pen stroke, etc.). We present a method to handle sparse dept…
End to End Vehicle Lateral Control Using a Single Fisheye Camera
Marin Toromanoff, Emilie Wirbel, Frédéric Wilhelm +3
Convolutional neural networks are commonly used to control the steering angle for autonomous cars. Most of the time, multiple long range cameras are used to generate lateral failur…