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25th Eurographics Conference on visualization, EuroVis 2023

作者： Becker, F. Ertl, T. University of Stuttgart Institute for Visualization and Interactive Systems Germany

ISBN: (纸本)9783038682202

When users work with interactive visualization systems, they get to see more accessible representations of raw data and interact with these, e.g. by filtering the data or modifying the visualization parameters like color. Internal representations such as hunches about trends, outliers or data points of interest, relationships and more are usually not visualized and integrated in systems, i.e. they are not externalized. In addition, how externalizations in visualization systems can affect users in terms of memory, post-analysis recall, speed or analysis quality is not yet completely understood. We present a visualization-agnostic externalization framework that lets users annotate visualizations, automatically connect them to related data and store them for later retrieval. In addition, we conducted a pilot study to test the framework’s usability and users’ recall of exploratory analysis results. In two tasks, one without and one with annotation features available, we asked participants to answer a question with the help of visualizations and report their findings with concrete examples afterwards. Qualitative analysis of the summaries showed that there are only minor differences in terms of detail or completeness, which we suspect is due to the short task time and consequently more shallow analyses made by participants. We discuss how to improve our framework’s usability and modify our study design for future research to gain more insight into externalization effects on post-analysis recall. © 2023 The Authors.

关键词： visualization

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Augmented Reality in Service of Human Operations on the Moon: Insights from a Virtual Testbed

Augmented Reality in Service of Human Operations on the Moon...

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Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing systems, CHI EA 2023

作者： Becker, Leonie Nilsson, Tommy Demedeiros, Paul Rometsch, Flavie Software for Space Systems and Interactive Visualization Brunswick Germany Cologne Germany Noordwijk Netherlands

ISBN: (纸本)9781450394222

Future astronauts living and working on the Moon will face extreme environmental conditions impeding their operational safety and performance. While it has been suggested that Augmented Reality (AR) Head-Up Displays (HUDs) could potentially help mitigate some of these adversities, the applicability of AR in the unique lunar context remains underexplored. To address this limitation, we have produced an accurate representation of the lunar setting in virtual reality (VR) which then formed our testbed for the exploration of prospective operational scenarios with aerospace experts. Herein we present findings based on qualitative reflections made by the first 6 study participants. AR was found instrumental in several use cases, including the support of navigation and risk awareness. Major design challenges were likewise identified, including the importance of redundancy and contextual appropriateness. Drawing on these findings, we conclude by outlining directions for future research aimed at developing AR-based assistive solutions tailored to the lunar setting. © 2023 Owner/Author.

关键词： Virtual reality

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Efficient Sphere Rendering Revisited

Efficient Sphere Rendering Revisited

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23rd Eurographics Symposium on Parallel Graphics and visualization, EGPGV 2023

作者： Gralka, P. Reina, G. Ertl, T. University of Stuttgart Visualization Research Center Germany University of Stuttgart Institute for Visualization and Interactive Systems Germany

ISBN: (纸本)9783038682158

Glyphs are an intuitive way of displaying the results of atomistic simulations, usually as spheres. Raycasting of camera-aligned billboards is considered the state-of-the-art technique to render large sets of spheres in a rasterization-based pipeline since the approach was first proposed by Gumhold. Over time various acceleration techniques have been proposed, such as the rendering of point primitives as billboards, which are trivial to rasterize and avoid a high workload in the vertex pipeline. Other techniques attempt to optimize data upload and access patterns in shader programs, both relevant aspects for dynamic data. Recent advances in graphics hardware raise the question of whether these optimizations are still valid. We evaluate several rendering and data access scheme combinations on real-world datasets and derive recommendations for efficient rasterization-based sphere rendering. © 2023 The Authors.

关键词： Spheres

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Detection Defenses: An Empty Promise against Adversarial Patch Attacks on Optical Flow

Detection Defenses: An Empty Promise against Adversarial Pat...

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IEEE Workshop on Applications of Computer Vision (WACV)

作者： Erik Scheurer Jenny Schmalfuss Alexander Lis Andrés Bruhn Institute for Visualization and Interactive Systems University of Stuttgart

Adversarial patches undermine the reliability of optical flow predictions when placed in arbitrary scene locations. Therefore, they pose a realistic threat to real-world motion detection and its downstream applications. Potential remedies are defense strategies that detect and remove adversarial patches, but their influence on the underlying motion prediction has not been investigated. In this paper, we thoroughly examine the currently available detect-and-remove defenses ILP and LGS for a wide selection of state-of-the-art optical flow methods, and illuminate their side effects on the quality and robustness of the final flow predictions. In particular, we implement defense-aware attacks to investigate whether current defenses are able to withstand attacks that take the defense mechanism into account. Our experiments yield two surprising results: Detect-and-remove defenses do not only lower the optical flow quality on benign scenes, in doing so, they also harm the robustness under patch attacks for all tested optical flow methods except FlowNetC. As currently employed detect-and-remove defenses fail to deliver the promised adversarial robustness for optical flow, they evoke a false sense of security. The code is available at https://***/cvstuttgart/DetectionDefenses.

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A language to analyze, describe, and explore collections of visual art

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Visual Computing for Industry,Biomedicine,and Art 2021年第1期4卷 29-49页

作者： Hermann Pflüger Institute for Visualization and Interactive Systems University of Stuttgart70569 StuttgartGermany

A vast quantity of art in existence today is inaccessible to *** people want to know the different types of art that exist,how individual works are connected,and how works of art are interpreted and discussed in the context of other works,they must utilize means other than simply viewing the ***,this paper proposes a language to analyze,describe,and explore collections of visual art(LadeCA).LadeCA combines human interpretation and automatic analyses of images,allowing users to assess collections of visual art without viewing every image in *** paper focuses on the lexical base of *** also outlines how collections of visual art can be analyzed,described,and explored using a LadeCA ***,the relationship between LadeCA and indexing systems,such as ICONCLASS or AAT,is demonstrated,and ways in which LadeCA and indexing systems can complement each other are highlighted.

关键词： Collections of visual art Visual computing Personalized digital libraries Digital humanities Semantics

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VD-GR: Boosting Visual Dialog with Cascaded Spatial-Temporal Multi-Modal GRaphs

VD-GR: Boosting Visual Dialog with Cascaded Spatial-Temporal...

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IEEE Workshop on Applications of Computer Vision (WACV)

作者： Adnen Abdessaied Lei Shi Andreas Bulling Institute for Visualization and Interactive Systems University of Stuttgart Germany

We propose $\mathbb{V}\mathbb{D}{\text{ - }}\mathbb{G}\mathbb{R}$ – a novel visual dialog model that combines pre-trained language models (LMs) with graph neural networks (GNNs). Prior works mainly focused on one class of models at the expense of the other, thus missing out on the opportunity of combining their respective benefits. At the core of $\mathbb{V}\mathbb{D}{\text{ - }}\mathbb{G}\mathbb{R}$ is a novel integration mechanism that alternates between spatial-temporal multi-modal GNNs and BERT layers, and that covers three distinct contributions: First, we use multi-modal GNNs to process the features of each modality (image, question, and dialog history) and exploit their local structures before performing BERT global attention. Second, we propose hub-nodes that link to all other nodes within one modality graph, allowing the model to propagate information from one GNN (modality) to the other in a cascaded manner. Third, we augment the BERT hidden states with fine-grained multi-modal GNN features before passing them to the next $\mathbb{V}\mathbb{D}{\text{ - }}\mathbb{G}\mathbb{R}$ layer. Evaluations on VisDial v1.0, VisDial v0.9, VisDialConv, and VisPro show that $\mathbb{V}\mathbb{D}{\text{ - }}\mathbb{G}\mathbb{R}$ achieves new state-of-the-art results across all four datasets.

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Spring: A High-Resolution High-Detail Dataset and Benchmark for Scene Flow, Optical Flow and Stereo

Spring: A High-Resolution High-Detail Dataset and Benchmark ...

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Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Lukas Mehl Jenny Schmalfuss Azin Jahedi Yaroslava Nalivayko Andrés Bruhn Institute for Visualization and Interactive Systems University of Stuttgart

While recent methods for motion and stereo estimation recover an unprecedented amount of details, such highly detailed structures are neither adequately reflected in the data of existing benchmarks nor their evaluation methodology. Hence, we introduce Spring - a large, high-resolution, high-detail, computer-generated benchmark for scene flow, optical flow, and stereo. Based on rendered scenes from the open-source Blender movie “Spring”, it provides photo-realistic HD datasets with state-of-the-art visual effects and ground truth training data. Furthermore, we provide a website to upload, analyze and compare results. Using a novel evaluation methodology based on a super-resolved UHD ground truth, our Spring benchmark can assess the quality of fine structures and provides further detailed performance statistics on different image regions. Regarding the number of ground truth frames, Spring is 60× larger than the only scene flow benchmark, KITTI 2015, and 15× larger than the well-established MPI Sintel optical flow benchmark. Initial results for recent methods on our benchmark show that estimating fine details is indeed challenging, as their accuracy leaves significant room for improvement. The Spring benchmark and the corresponding datasets are available at http://***.

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Distracting Downpour: Adversarial Weather Attacks for Motion Estimation

Distracting Downpour: Adversarial Weather Attacks for Motion...

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International Conference on Computer Vision (ICCV)

作者： Jenny Schmalfuss Lukas Mehl Andrés Bruhn Institute for Visualization and Interactive Systems University of Stuttgart

Current adversarial attacks on motion estimation, or optical flow, optimize small per-pixel perturbations, which are unlikely to appear in the real world. In contrast, adverse weather conditions constitute a much more realistic threat scenario. Hence, in this work, we present a novel attack on motion estimation that exploits adversarially optimized particles to mimic weather effects like snowflakes, rain streaks or fog clouds. At the core of our attack framework is a differentiable particle rendering system that integrates particles (i) consistently over multiple time steps (ii) into the 3D space (iii) with a photo-realistic appearance. Through optimization, we obtain adversarial weather that significantly impacts the motion estimation. Surprisingly, methods that previously showed good robustness towards small per-pixel perturbations are particularly vulnerable to adversarial weather. At the same time, augmenting the training with non-optimized weather increases a method’s robustness towards weather effects and improves generalizability at almost no additional cost. Our code is available at https://***/cv-stuttgart/DistractingDownpour.

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Detection Defenses: An Empty Promise against Adversarial Patch Attacks on Optical Flow

arXiv

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arXiv 2023年

作者： Scheurer, Erik Schmalfuss, Jenny Lis, Alexander Bruhn, Andrés Institute for Visualization and Interactive Systems University of Stuttgart Germany

关键词： Optical flows

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Spring: A High-Resolution High-Detail Dataset and Benchmark for Scene Flow, Optical Flow and Stereo

arXiv

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arXiv 2023年

作者： Mehl, Lukas Schmalfuss, Jenny Jahedi, Azin Nalivayko, Yaroslava Bruhn, Andrés Institute for Visualization and Interactive Systems University of Stuttgart Germany

While recent methods for motion and stereo estimation recover an unprecedented amount of details, such highly detailed structures are neither adequately reflected in the data of existing benchmarks nor their evaluation methodology. Hence, we introduce Spring - a large, high-resolution, high-detail, computer-generated benchmark for scene flow, optical flow, and stereo. Based on rendered scenes from the open-source Blender movie "Spring", it provides photo-realistic HD datasets with state-of-the-art visual effects and ground truth training data. Furthermore, we provide a website to upload, analyze and compare results. Using a novel evaluation methodology based on a super-resolved UHD ground truth, our Spring benchmark can assess the quality of fine structures and provides further detailed performance statistics on different image regions. Regarding the number of ground truth frames, Spring is 60× larger than the only scene flow benchmark, KITTI 2015, and 15× larger than the well-established MPI Sintel optical flow benchmark. Initial results for recent methods on our benchmark show that estimating fine details is indeed challenging, as their accuracy leaves significant room for improvement. The Spring benchmark and the corresponding datasets are available at http://***. Copyright © 2023, The Authors. All rights reserved.

关键词： Benchmarking

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