99 citations · 99 across the 5 of their papers we have counts for
5 papers
Uncertainty-Aware Missing-Data Multimodal Latent for Fetal-Growth Analysis
Tiago Cortinhal, César Díaz-Parga, Gabriel Bernardino +1
Objective: Routine third-trimester examination yields fetal biometry, maternal, Doppler and fetal-cardiac measurements, acquired at clinical discretion and therefore often incomple…
Semantics-aware LiDAR-Only Pseudo Point Cloud Generation for 3D Object Detection
Tiago Cortinhal, Idriss Gouigah, Eren Erdal Aksoy
Although LiDAR sensors are crucial for autonomous systems due to providing precise depth information, they struggle with capturing fine object details, especially at a distance, du…
Depth- and Semantics-aware Multi-modal Domain Translation: Generating 3D Panoramic Color Images from LiDAR Point Clouds
Tiago Cortinhal, Eren Erdal Aksoy
This work presents a new depth- and semantics-aware conditional generative model, named TITAN-Next, for cross-domain image-to-image translation in a multi-modal setup between LiDAR…
Semantics-aware Multi-modal Domain Translation:From LiDAR Point Clouds to Panoramic Color Images
Tiago Cortinhal, Fatih Kurnaz, Eren Aksoy
In this work, we present a simple yet effective framework to address the domain translation problem between different sensor modalities with unique data formats. By relying only on…
SalsaNext: Fast, Uncertainty-aware Semantic Segmentation of LiDAR Point Clouds for Autonomous Driving
Tiago Cortinhal, George Tzelepis, Eren Erdal Aksoy
In this paper, we introduce SalsaNext for the uncertainty-aware semantic segmentation of a full 3D LiDAR point cloud in real-time. SalsaNext is the next version of SalsaNet [1] whi…