Search Results for author: Maximilian Denninger

Found 4 papers, 4 papers with code

3D Scene Reconstruction from a Single Viewport

1 code implementation ECCV 2020 Maximilian Denninger, Rudolph Triebel

To overcome the problem of reconstructing regions in 3D that are occluded in the 2D image, we propose to learn this information from synthetically generated high-resolution data.

3D Scene Reconstruction

RECALL: Rehearsal-free Continual Learning for Object Classification

1 code implementation29 Sep 2022 Markus Knauer, Maximilian Denninger, Rudolph Triebel

Our approach is called RECALL, as the network recalls categories by calculating logits for old categories before training new ones.

Classification Continual Learning +2

Learning to Localize in New Environments from Synthetic Training Data

1 code implementation9 Nov 2020 Dominik Winkelbauer, Maximilian Denninger, Rudolph Triebel

Our approach outperforms the 5-point algorithm using SIFT features on equally big images and additionally surpasses all previous learning-based approaches that were trained on different data.

Visual Localization

BlenderProc

4 code implementations25 Oct 2019 Maximilian Denninger, Martin Sundermeyer, Dominik Winkelbauer, Youssef Zidan, Dmitry Olefir, Mohamad Elbadrawy, Ahsan Lodhi, Harinandan Katam

BlenderProc is a modular procedural pipeline, which helps in generating real looking images for the training of convolutional neural networks.

3D Object Recognition Depth Image Estimation +3

Cannot find the paper you are looking for? You can Submit a new open access paper.