150 citations · 211 across the 18 of their papers we have counts for
6 papers · 1 filter
SOAC: Spatio-Temporal Overlap-Aware Multi-Sensor Calibration using Neural Radiance Fields
Quentin Herau, Nathan Piasco, Moussab Bennehar +5
In rapidly-evolving domains such as autonomous driving, the use of multiple sensors with different modalities is crucial to ensure high operational precision and stability. To corr…
Alignment-free HDR Deghosting with Semantics Consistent Transformer
Steven Tel, Zongwei Wu, Yulun Zhang +4
High dynamic range (HDR) imaging aims to retrieve information from multiple low-dynamic range inputs to generate realistic output. The essence is to leverage the contextual informa…
Object Segmentation by Mining Cross-Modal Semantics
Zongwei Wu, Jingjing Wang, Zhuyun Zhou +5
Multi-sensor clues have shown promise for object segmentation, but inherent noise in each sensor, as well as the calibration error in practice, may bias the segmentation accuracy.…
Mobile Mapping Mesh Change Detection and Update
Teng Wu, Bruno Vallet, Cédric Demonceaux
Mobile mapping, in particular, Mobile Lidar Scanning (MLS) is increasingly widespread to monitor and map urban scenes at city scale with unprecedented resolution and accuracy. The…
MOISST: Multimodal Optimization of Implicit Scene for SpatioTemporal calibration
Quentin Herau, Nathan Piasco, Moussab Bennehar +5
With the recent advances in autonomous driving and the decreasing cost of LiDARs, the use of multimodal sensor systems is on the rise. However, in order to make use of the informat…
HiDAnet: RGB-D Salient Object Detection via Hierarchical Depth Awareness
Zongwei Wu, Guillaume Allibert, Fabrice Meriaudeau +2
RGB-D saliency detection aims to fuse multi-modal cues to accurately localize salient regions. Existing works often adopt attention modules for feature modeling, with few methods e…