Search Results for author: Hendrik P. A. Lensch

Found 34 papers, 18 papers with code

DualAD: Disentangling the Dynamic and Static World for End-to-End Driving

no code implementations CVPR 2024 Simon Doll, Niklas Hanselmann, Lukas Schneider, Richard Schulz, Marius Cordts, Markus Enzweiler, Hendrik P. A. Lensch

State-of-the-art approaches for autonomous driving integrate multiple sub-tasks of the overall driving task into a single pipeline that can be trained in an end-to-end fashion by passing latent representations between the different modules.

Autonomous Driving

Iterative Cluster Harvesting for Wafer Map Defect Patterns

no code implementations23 Apr 2024 Alina Pleli, Simon Baeuerle, Michel Janus, Jonas Barth, Ralf Mikut, Hendrik P. A. Lensch

Unsupervised clustering of wafer map defect patterns is challenging because the appearance of certain defect patterns varies significantly.

Clustering Dimensionality Reduction

Disentangling representations of retinal images with generative models

no code implementations29 Feb 2024 Sarah Müller, Lisa M. Koch, Hendrik P. A. Lensch, Philipp Berens

Retinal fundus images play a crucial role in the early detection of eye diseases and, using deep learning approaches, recent studies have even demonstrated their potential for detecting cardiovascular risk factors and neurological disorders.

Disentanglement Image Generation

Visual Grounding of Inter-lingual Word-Embeddings

no code implementations8 Sep 2022 Wafaa Mohammed, Hassan Shahmohammadi, Hendrik P. A. Lensch, R. Harald Baayen

We obtained visually grounded vector representations for these languages and studied whether visual grounding on one or multiple languages improved the performance of embeddings on word similarity and categorization benchmarks.

Visual Grounding Word Embeddings +1

Diverse Video Captioning by Adaptive Spatio-temporal Attention

1 code implementation19 Aug 2022 Zohreh Ghaderi, Leonard Salewski, Hendrik P. A. Lensch

To generate proper captions for videos, the inference needs to identify relevant concepts and pay attention to the spatial relationships between them as well as to the temporal development in the clip.

Decoder Text Generation +1

Language with Vision: a Study on Grounded Word and Sentence Embeddings

1 code implementation17 Jun 2022 Hassan Shahmohammadi, Maria Heitmeier, Elnaz Shafaei-Bajestan, Hendrik P. A. Lensch, Harald Baayen

Our model effectively balances the interplay between language and vision by aligning textual embeddings with visual information while simultaneously preserving the distributional statistics that characterize word usage in text corpora.

Sentence Sentence Embeddings +3

CLEVR-X: A Visual Reasoning Dataset for Natural Language Explanations

1 code implementation5 Apr 2022 Leonard Salewski, A. Sophia Koepke, Hendrik P. A. Lensch, Zeynep Akata

We present baseline results for generating natural language explanations in the context of VQA using two state-of-the-art frameworks on the CLEVR-X dataset.

Explanation Generation Question Answering +3

Learning Zero-Shot Multifaceted Visually Grounded Word Embeddings via Multi-Task Training

1 code implementation CoNLL (EMNLP) 2021 Hassan Shahmohammadi, Hendrik P. A. Lensch, R. Harald Baayen

The general approach is to embed both textual and visual information into a common space -the grounded space-confined by an explicit relationship between both modalities.

Multi-Task Learning Word Embeddings

NeRD: Neural Reflectance Decomposition from Image Collections

1 code implementation ICCV 2021 Mark Boss, Raphael Braun, Varun Jampani, Jonathan T. Barron, Ce Liu, Hendrik P. A. Lensch

This problem is inherently more challenging when the illumination is not a single light source under laboratory conditions but is instead an unconstrained environmental illumination.

Depth Prediction Image Relighting +3

Latent State Inference in a Spatiotemporal Generative Model

no code implementations21 Sep 2020 Matthias Karlbauer, Tobias Menge, Sebastian Otte, Hendrik P. A. Lensch, Thomas Scholten, Volker Wulfmeyer, Martin V. Butz

Knowledge about the hidden factors that determine particular system dynamics is crucial for both explaining them and pursuing goal-directed interventions.

Causal Inference Time Series +1

Inferring, Predicting, and Denoising Causal Wave Dynamics

no code implementations19 Sep 2020 Matthias Karlbauer, Sebastian Otte, Hendrik P. A. Lensch, Thomas Scholten, Volker Wulfmeyer, Martin V. Butz

The novel DISTributed Artificial neural Network Architecture (DISTANA) is a generative, recurrent graph convolution neural network.


Two-shot Spatially-varying BRDF and Shape Estimation

1 code implementation CVPR 2020 Mark Boss, Varun Jampani, Kihwan Kim, Hendrik P. A. Lensch, Jan Kautz

Extensive experiments on both synthetic and real-world datasets show that our network trained on a synthetic dataset can generalize well to real-world images.

Vocal Bursts Valence Prediction

GGNN: Graph-based GPU Nearest Neighbor Search

1 code implementation2 Dec 2019 Fabian Groh, Lukas Ruppert, Patrick Wieschollek, Hendrik P. A. Lensch

Approximate nearest neighbor (ANN) search in high dimensions is an integral part of several computer vision systems and gains importance in deep learning with explicit memory representations.

Single Image BRDF Parameter Estimation with a Conditional Adversarial Network

no code implementations11 Oct 2019 Mark Boss, Hendrik P. A. Lensch

Creating plausible surfaces is an essential component in achieving a high degree of realism in rendering.


Flex-Convolution (Million-Scale Point-Cloud Learning Beyond Grid-Worlds)

1 code implementation20 Mar 2018 Fabian Groh, Patrick Wieschollek, Hendrik P. A. Lensch

Traditional convolution layers are specifically designed to exploit the natural data representation of images -- a fixed and regular grid.

Classify 3D Point Clouds Semantic Segmentation

Learning Blind Motion Deblurring

1 code implementation ICCV 2017 Patrick Wieschollek, Michael Hirsch, Bernhard Schölkopf, Hendrik P. A. Lensch

As handheld video cameras are now commonplace and available in every smartphone, images and videos can be recorded almost everywhere at anytime.


Efficient Large-scale Approximate Nearest Neighbor Search on the GPU

1 code implementation CVPR 2016 Patrick Wieschollek, Oliver Wang, Alexander Sorkine-Hornung, Hendrik P. A. Lensch

We present a new approach for efficient approximate nearest neighbor (ANN) search in high dimensional spaces, extending the idea of Product Quantization.

Quantization Re-Ranking

Backpropagation Training for Fisher Vectors within Neural Networks

no code implementations8 Feb 2017 Patrick Wieschollek, Fabian Groh, Hendrik P. A. Lensch

Fisher-Vectors (FV) encode higher-order statistics of a set of multiple local descriptors like SIFT features.

Will People Like Your Image? Learning the Aesthetic Space

2 code implementations16 Nov 2016 Katharina Schwarz, Patrick Wieschollek, Hendrik P. A. Lensch

Rating how aesthetically pleasing an image appears is a highly complex matter and depends on a large number of different visual factors.

Learning Robust Video Synchronization without Annotations

no code implementations19 Oct 2016 Patrick Wieschollek, Ido Freeman, Hendrik P. A. Lensch

Aligning video sequences is a fundamental yet still unsolved component for a broad range of applications in computer graphics and vision.

Video Alignment Video Synchronization

Transfer Learning for Material Classification using Convolutional Networks

no code implementations20 Sep 2016 Patrick Wieschollek, Hendrik P. A. Lensch

Specifically, transfer learning from the task of object recognition is exploited to more effectively train good features for material classification.

Classification Descriptive +5

Robust Deep-Learning-Based Road-Prediction for Augmented Reality Navigation Systems

no code implementations31 May 2016 Matthias Limmer, Julian Forster, Dennis Baudach, Florian Schüle, Roland Schweiger, Hendrik P. A. Lensch

The proposed approach reliably detects roads with and without lane markings and thus increases the robustness and availability of road course estimations and augmented reality navigation.

Infrared Colorization Using Deep Convolutional Neural Networks

2 code implementations8 Apr 2016 Matthias Limmer, Hendrik P. A. Lensch

This paper proposes a method for transferring the RGB color spectrum to near-infrared (NIR) images using deep multi-scale convolutional neural networks.


Scalable Structure From Motion for Densely Sampled Videos

no code implementations CVPR 2015 Benjamin Resch, Hendrik P. A. Lensch, Oliver Wang, Marc Pollefeys, Alexander Sorkine-Hornung

Videos consisting of thousands of high resolution frames are challenging for existing structure from motion (SfM) and simultaneous-localization and mapping (SLAM) techniques.

Pose Estimation Simultaneous Localization and Mapping

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