Larissa T. Triess

Publication Activity (10 Years)

Years Active: 2019-2022
Publications (10 Years): 13

Top Topics

Top Venues

Int. J. Comput. Vis.

Publications

Larissa T. Triess, Andre Bühler, David Peter, Fabian B. Flohr, J. Marius Zöllner
Point Cloud Generation with Continuous Conditioning. CoRR (2022)
Larissa T. Triess, Christoph B. Rist, David Peter, J. Marius Zöllner
A Realism Metric for Generated LiDAR Point Clouds. CoRR (2022)
Larissa T. Triess, Andre Bühler, David Peter, Fabian B. Flohr, Marius Zöllner
Point Cloud Generation with Continuous Conditioning. AISTATS (2022)
Larissa T. Triess, Christoph B. Rist, David Peter, J. Marius Zöllner
A Realism Metric for Generated LiDAR Point Clouds. Int. J. Comput. Vis. 130 (12) (2022)
Larissa T. Triess, David Peter, Stefan A. Baur, J. Marius Zöllner
Quantifying point cloud realism through adversarially learned latent representations. CoRR (2021)
Larissa T. Triess, Mariella Dreissig, Christoph B. Rist, J. Marius Zöllner
A Survey on Deep Domain Adaptation for LiDAR Perception. IV Workshops (2021)
Larissa T. Triess, Mariella Dreissig, Christoph B. Rist, J. Marius Zöllner
A Survey on Deep Domain Adaptation for LiDAR Perception. CoRR (2021)
Larissa T. Triess, David Peter, J. Marius Zöllner
Semi-Local Convolutions for LiDAR Scan Processing. CoRR (2021)
Larissa T. Triess, David Peter, Stefan A. Baur, J. Marius Zöllner
Quantifying Point Cloud Realism Through Adversarially Learned Latent Representations. GCPR (2021)
Larissa T. Triess, David Peter, Christoph B. Rist, J. Marius Zöllner
Scan-based Semantic Segmentation of LiDAR Point Clouds: An Experimental Study. CoRR (2020)
Larissa T. Triess, David Peter, Christoph B. Rist, J. Marius Zöllner
Scan-based Semantic Segmentation of LiDAR Point Clouds: An Experimental Study. IV (2020)
Larissa T. Triess, David Peter, Christoph B. Rist, Markus Enzweiler, J. Marius Zöllner
CNN-based synthesis of realistic high-resolution LiDAR data. CoRR (2019)
Larissa T. Triess, David Peter, Christoph B. Rist, Markus Enzweiler, J. Marius Zöllner
CNN-based synthesis of realistic high-resolution LiDAR data. IV (2019)