News

Augmented Vision presented 4 papers at the ICPRAM conference

The researchers of the Augmented Vision department have presented 4 papers at the ICPRAM 2025 conference taking place Feb 23 – 25, 2025 in Porto, Portugal.

The International Conference on Pattern Recognition Applications and Methods (ICPRAM) is a point of contact between researchers and engineers working on Pattern Recognition, both from a theoretical and application perspective.

The presented papers are:

Domain-Incremental Semantic Segmentation for Autonomous Driving under Adverse Driving Conditions
Shishir Muralidhara, René Schuster, Didier Stricker

1D-DiffNPHR: 1D Diffusion Neural Parametric Head Reconstruction using a single image
Pragati Jaiswal, Tewodros Amberbir Habtegebrial, Didier Stricker

HI^2: Sparse-View 3D Object Reconstruction with a Hybrid Implicit Initialization
Pragati Jaiswal, Didier Stricker

Object-Centric 2D Gaussian Splatting: Background Removal and Occlusion-Aware Pruning for Compact Object Models
Marcel Rogge, Didier Stricker

The paper “HI^2: Sparse-View 3D Object Reconstruction with a Hybrid Implicit Initialization” was a nominee for the best paper award.

Congratulations to all the authors!

Contact: René Schuster, Didier Stricker

Augmented Vision presented 4 papers at the WACV conference

The researchers of the department Augmented Vision have presented 4 papers at WACV 2025 conference taking place Feb 28 – Mar 4, 2025 in Tucson, Arizona, USA.

The IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) one of the three major Computer Vision conferences organized by TCPAMI.

The 4 papers are:

“Uni-SLAM: Uncertainty-Aware Neural Implicit SLAM for Real-Time Dense Indoor Scene Reconstruction” Shaoxiang Wang, Yaxu Xie, Chun-Peng Chang, Christen Millerdurai, Alain Pagani, Didier Stricker

“Modality-Incremental Learning with Disjoint Relevance Mapping Networks for Image-based Semantic Segmentation”, Niharika Hegde, Shishir Muralidhara, René Schuster, Didier Stricker

“AnonyNoise: Anonymizing Event Data with Smart Noise to Outsmart Re-Identification and Preserve Privacy”, Katharina Bendig, René Schuster, Nicole Thiemer, Karen Joisten, Didier Stricker

“Beyond Boxes: Mask-Guided Spatio-Temporal Feature Aggregation for Video Object Detection”, Khurram Azeem Hashmi, Talha Uddin Sheikh, Didier Stricker, Muhammad Zeshan Afzal

Congratulations to the authors for this great achievement!

Contact: Alain Pagani, René Schuster, Zeshan Afzal

Contact: Alain Pagani, René Schuster, Zeshan Afzal

Paper accepted to ECCV 2024

We are very happy that our paper “CLEO: Continual Learning of Evolving Ontologies” has been accepted to the European Conference on Computer Vision (ECCV). A preprint of our work can be found here. A short video is available on YouTube. The paper is a joint work with ZF Friedrichshafen AG and describes some results of our collaboration.

Paper published in the International Journal of Computer Vision (IJCV)

We are proud to announce that our paper “RMS-FlowNet++: Efficient and Robust Multi-scale Scene Flow Estimation for Large-Scale Point Clouds” by Ramy Battrawy, René Schuster, and Didier Stricker has been published in the International Journal of Computer Vision (IJCV). The online version of the paper can be found here a preprint is available here. The paper extends our previous work on efficient scene flow estimation in dense point clouds that has been published at ICRA 2022.

René Schuster receives an Outstanding Reviewer Award from the organizing committee of the SAIAD workshop

The 6th workshop on Safe Artificial Intelligence for All Domains was held this year in conjunction with CVPR in Seattle. René Schuster is a permanent member of the program committee since 2020.

Best Poster Award at BMVC 2023

Congratulations to Ramy Battrawy for his best poster Award at BMVC 2023, https://bmvc2023.org, for his paper.

“EgoFlowNet: Non-Rigid Scene Flow from Point Clouds with Ego-Motion Support”

Ramy Battrawy (DFKI),* René Schuster (DFKI), Didier Stricker (DFKI), BMVC 2023

Please check the paper and the video under: https://proceedings.bmvc2023.org/441/