171 citations · 283 across the 29 of their papers we have counts for
8 papers · 1 filter
Dual Exposure Stereo for Extended Dynamic Range 3D Imaging
Juhyung Choi, Jinnyeong Kim, Seokjun Choi +5
Achieving robust stereo 3D imaging under diverse illumination conditions is an important however challenging task, due to the limited dynamic ranges (DRs) of cameras, which are sig…
Polarization Wavefront Lidar: Learning Large Scene Reconstruction from Polarized Wavefronts
Dominik Scheuble, Chenyang Lei, Seung-Hwan Baek +2
Lidar has become a cornerstone sensing modality for 3D vision, especially for large outdoor scenarios and autonomous driving. Conventional lidar sensors are capable of providing ce…
Gated Fields: Learning Scene Reconstruction from Gated Videos
Andrea Ramazzina, Stefanie Walz, Pragyan Dahal +2
Reconstructing outdoor 3D scenes from temporal observations is a challenge that recent work on neural fields has offered a new avenue for. However, existing methods that recover sc…
HINT: Learning Complete Human Neural Representations from Limited Viewpoints
Alessandro Sanvito, Andrea Ramazzina, Stefanie Walz +2
No augmented application is possible without animated humanoid avatars. At the same time, generating human replicas from real-world monocular hand-held or robotic sensor setups is…
Real-Time Environment Condition Classification for Autonomous Vehicles
Marco Introvigne, Andrea Ramazzina, Stefanie Walz +2
Current autonomous driving technologies are being rolled out in geo-fenced areas with well-defined operation conditions such as time of operation, area, weather conditions and road…
Cross-spectral Gated-RGB Stereo Depth Estimation
Samuel Brucker, Stefanie Walz, Mario Bijelic +1
Gated cameras flood-illuminate a scene and capture the time-gated impulse response of a scene. By employing nanosecond-scale gates, existing sensors are capable of capturing mega-p…
Radar Fields: Frequency-Space Neural Scene Representations for FMCW Radar
David Borts, Erich Liang, Tim Brödermann +9
Neural fields have been broadly investigated as scene representations for the reproduction and novel generation of diverse outdoor scenes, including those autonomous vehicles and r…
Inverse Neural Rendering for Explainable Multi-Object Tracking
Julian Ost, Tanushree Banerjee, Mario Bijelic +1
Today, most methods for image understanding tasks rely on feed-forward neural networks. While this approach has allowed for empirical accuracy, efficiency, and task adaptation via…