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DFKI AV – Stellantis Collaboration on Radar-Camera Fusion – Papers at GCPR and EUSIPCO

DFKI Augmented Vision is collaborating with Stellantis on the topic of Radar-Camera Fusion for Automotive Object Detection using Deep Learning. Recently, two new publications were accepted to the GCPR 2023 and EUSIPCO 2023 conferences.

The 2 new publications are:

1.  Cross-Dataset Experimental Study of Radar-Camera Fusion in Bird’s-Eye ViewProceedings of the 31st. European Signal Processing Conference (EUSIPCO-2023), September 4-8, Helsinki, Finland, IEEE, 2023.

Lukas Stefan Stäcker, Philipp Heidenreich, Jason Rambach, Didier Stricker

This paper investigates the influence of the training dataset and transfer learning on camera-radar fusion approaches, showing that while the camera branch needs large and diverse training data, the radar branch benefits more from a high-performance radar.

Cross-Dataset Experimental Study of Radar-Camera Fusion in Bird’s-Eye View

2. RC-BEVFusion: A Plug-In Module for Radar-Camera Bird’s Eye View Feature FusionProceedings of. Annual Symposium of the German Association for Pattern Recognition (DAGM-2023), September 19-22, Heidelberg, BW, Germany, DAGM, 9/2023.

Lukas Stefan Stäcker, Shashank Mishra, Philipp Heidenreich, Jason Rambach, Didier Stricker

This paper introduces a new Bird’s Eye view fusion network architecture for camera-radar fusion for 3D object detection that performs favorably on the NuScenes dataset benchmark.

RC-BEVFusion: A Plug-In Module for Radar-Camera Bird’s Eye View Feature Fusion

Contacts: Dr. Jason Rambach

ICCV 2023: 4 papers accepted

We are happy to announce that the Augmented Vision group will present 4 papers in the upcoming ICCV 2023 Conference, 2-6 October, Paris, France. The IEEE/CVF International Conference in Computer Vision (ICCV) is the premier international computer vision event. Homepage: https://iccv2023.thecvf.com/  

The 4 accepted papers are:

  1. U-RED: Unsupervised 3D Shape Retrieval and Deformation for Partial Point Clouds
    Yan Di, Chenyangguang Zhang, Ruida Zhang, Fabian Manhardt, Yongzhi Su, Jason Raphael Rambach, Didier Stricker, Xiangyang Ji, Federico Tombari
  2. FeatEnHancer: Enhancing Hierarchical Features for Object Detection and Beyond Under Low-Light Vision. Khurram Azeem Hashmi, Goutham Kallempudi, Didier Stricker, Muhammad Zeshan Afzal
  3. Introducing Language Guidance in Prompt-based Continual Learning Muhammad Gulzain Ali Khan, Muhammad Ferjad Naeem; Luc Van Gool; Federico  Tombari; Didier Stricker, Muhammad Zeshan Afzal
  4. DELO: Deep Evidential LiDAR Odometry using Partial Optimal Transport Sk Aziz Ali, Djamila Aouada, Gerd Reis, Didier Stricker