research
∙
06/15/2023
Challenges of Using Real-World Sensory Inputs for Motion Forecasting in Autonomous Driving
Motion forecasting plays a critical role in enabling robots to anticipat...
share
research
∙
12/15/2022
Unsupervised Object Localization: Observing the Background to Discover Objects
Recent advances in self-supervised visual representation learning have p...
research
∙
11/22/2022
OCTET: Object-aware Counterfactual Explanations
Nowadays, deep vision models are being widely deployed in safety-critica...
research
∙
06/27/2022
LaRa: Latents and Rays for Multi-Camera Bird's-Eye-View Semantic Segmentation
Recent works in autonomous driving have widely adopted the bird's-eye-vi...
research
∙
11/17/2021
STEEX: Steering Counterfactual Explanations with Semantics
As deep learning models are increasingly used in safety-critical applica...
research
∙
09/16/2021
Raising context awareness in motion forecasting
Learning-based trajectory prediction models have encountered great succe...
research
∙
09/08/2021
LiDARTouch: Monocular metric depth estimation with a few-beam LiDAR
Vision-based depth estimation is a key feature in autonomous systems, wh...
research
∙
01/13/2021
Explainability of vision-based autonomous driving systems: Review and challenges
This survey reviews explainability methods for vision-based self-driving...
research
∙
12/09/2020
Driving Behavior Explanation with Multi-level Fusion
In this era of active development of autonomous vehicles, it becomes cru...
research
∙
11/13/2020
Transductive Zero-Shot Learning using Cross-Modal CycleGAN
In Computer Vision, Zero-Shot Learning (ZSL) aims at classifying unseen ...
research
∙
02/07/2020
Incorporating Visual Semantics into Sentence Representations within a Grounded Space
Language grounding is an active field aiming at enriching textual repres...
research
∙
04/24/2019
Context-Aware Zero-Shot Learning for Object Recognition
Zero-Shot Learning (ZSL) aims at classifying unlabeled objects by levera...
research
∙
11/09/2017
