no code implementations • 31 Mar 2024 • Mubariz Zaffar, Liangliang Nan, Julian F. P. Kooij
In Visual Place Recognition (VPR) the pose of a query image is estimated by comparing the image to a map of reference images with known reference poses.
no code implementations • 20 Feb 2024 • Ignacio Roldan, Andras Palffy, Julian F. P. Kooij, Dariu M. Gavrila, Francesco Fioranelli, Alexander Yarovoy
In this paper, we address the limitations of traditional constant false alarm rate (CFAR) target detectors in automotive radars, particularly in complex urban environments with multiple objects that appear as extended targets.
1 code implementation • 8 Dec 2023 • Nail Ibrahimli, Julian F. P. Kooij, Liangliang Nan
We introduce MuVieCAST, a modular multi-view consistent style transfer network architecture that enables consistent style transfer between multiple viewpoints of the same scene.
no code implementations • 25 Sep 2023 • Shiming Wang, Holger Caesar, Liangliang Nan, Julian F. P. Kooij
To validate its effectiveness, we compare UniBEV to state-of-the-art BEVFusion and MetaBEV on nuScenes over all sensor input combinations.
no code implementations • 9 May 2023 • Jetze T. Schuurmans, Kim Batselier, Julian F. P. Kooij
While scaling the approximation error commonly is used to account for the different sizes of layers, the average correlation across layers is smaller than across all choices (i. e. layers, decompositions, and level of compression) before fine-tuning.
1 code implementation • 9 Mar 2023 • Zimin Xia, Olaf Booij, Julian F. P. Kooij
The Localization Decoder produces a dense probability distribution in a coarse-to-fine manner with a novel Localization Matching Upsampling module.
1 code implementation • CVPR 2023 • Ted Lentsch, Zimin Xia, Holger Caesar, Julian F. P. Kooij
We propose SliceMatch, which consists of ground and aerial feature extractors, feature aggregators, and a pose predictor.
no code implementations • 23 Nov 2022 • Thomas M. Hehn, Julian F. P. Kooij, Dariu M. Gavrila
Various state-of-the-art self-supervised visual representation learning approaches take advantage of data from multiple sensors by aligning the feature representations across views and/or modalities.
1 code implementation • 17 Aug 2022 • Zimin Xia, Olaf Booij, Marco Manfredi, Julian F. P. Kooij
Given a ground-level color image and a satellite patch that contains the local surroundings, the task is to identify the location of the ground camera within the satellite patch.
1 code implementation • 30 Jul 2020 • Yannick Schulz, Avinash Kini Mattar, Thomas M. Hehn, Julian F. P. Kooij
A novel method is presented to classify if and from what direction a vehicle is approaching before it is visible, using as input Direction-of-Arrival features that can be efficiently computed from the streaming microphone array data.
1 code implementation • 25 Apr 2020 • Andras Palffy, Jiaao Dong, Julian F. P. Kooij, Dariu M. Gavrila
In experiments on a real-life dataset we demonstrate that our method outperforms the state-of-the-art methods both target- and object-wise by reaching an average of 0. 70 (baseline: 0. 68) target-wise and 0. 56 (baseline: 0. 48) object-wise F1 score.
no code implementations • 27 Oct 2018 • Frank Hafner, Amran Bhuiyan, Julian F. P. Kooij, Eric Granger
Person re-identification is a key challenge for surveillance across multiple sensors.