1,720,982 research outputs found
Lanelet2 for nuScenes: Map Dataset
No full textLanelet2 maps for the nuScenes dataset, which enable the usage of diverse map-based anchor paths and spatial semantic information. For details see our paper and project page. We also provide a pip package to facilitate the usage.
The maps were generated automatically and subsequently manually refined.
If you use this resource for scientific research, please consider citing
@InProceedings{naumannHertleinLanelet2NuScenes2023,
author = {Naumann, Alexander and Hertlein, Felix and Grimm, Daniel and Zipfl, Maximilian and Thoma, Steffen and Rettinger, Achim and Halilaj, Lavdim and Luettin, Juergen and Schmid, Stefan and Caesar, Holger},
title = {Lanelet2 for nuScenes: Enabling Spatial Semantic Relationships and Diverse Map-Based Anchor Paths},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2023},
pages = {3247-3256}
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
3D Scene Compression for Autonomous Driving using Neural Radiance Fields
No full textNeural Radiance Fields (NeRFs) have showcased remarkable effectiveness in capturing complex 3D scenes and synthesizing novel viewpoints. By inherently capturing the entire scene in a compact representation, they offer a promising avenue for applications such as simulators, where efficient storage of real-world data, fast rendering and dynamic generation of new content are crucial. However, the potential for compression in NeRFs has been largely neglected in the existing literature. Moreover, the practical deployment of NeRFs in real-world scenarios, including simulators, faces significant obstacles such as constraints in training time, rendering speed, and scalability to large scenes. While recent advancements have tackled some of these hurdles individually, none have offered a comprehensive solution. In this paper, we introduce a new NeRF architecture based on a textured polygon-based method and augment this architecture by integrating encodings to expedite training. Additionally, we introduce learned pose refinement and an appearance embedding to enhance scalability to larger scenes. Through experimentation on the nuScenes dataset, we demonstrate that our method achieves competitive reconstruction performance with existing techniques while surpassing them in rendering speed. Furthermore, in terms of compression, our findings indicate that our method achieves competitive compression rates comparable to image-based compression techniques, while also enabling novel-view synthesis. This underscores its potential utility in applications like simulators.Mechanical Engineering | Vehicle Engineering | Cognitive Robotic
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
LiDAR Tokenizer
Get PDFV blízké budoucnosti budou LiDARy důležitou součástí bezpečnostních systémů moderních vozů společně s dalšími senzory, jako jsou kamery. Abychom data z LiDARu plně využili tím, že umožníme jejich použití uvnitř Transformer modelů, musí být data rozdělena na jednotlivé díly, nazývané tokeny. V této práci zkoumáme dva autoenkodéry na tokenizaci LiDARových dat, jeden využívající 2D zobrazení vzdáleností a druhý 3D voxely k jejich reprezentaci, a zaměřujeme se na jejich způsoby kvantizace a kódování. Modely porovnáváme a vyhodnocujeme na úloze komprese a následné rekonstrukce dat z datasetů nuScenes a FrontCam. Abychom demonstrovali možnosti využití natrénovaných tokenizérů, rozšířili jsme jimi Transformer model pro generování obrázků MaskGIT na multimodální model generující páry obrázků a LiDARových skenů. S tímto modelem generujeme slibně vypadající výstupy a ukazujeme jeho další využití, jako je generování obrázků podmíněných LiDARovým skenem.In the near future, LiDAR sensors will play an important role in the safety systems of modern vehicles, complementing other sensors such as cameras. To fully utilize LiDAR point clouds by enabling their usage in Transformer models, the point clouds need to be chunked into separate data units called tokens. In this thesis, we investigate two autoencoder models for LiDAR tokenization using the 2D range image and 3D voxel representations of point clouds, focusing on the quantization method and codebook settings they use. We compare and evaluate the models on the proxy task of point cloud compression and reconstruction using the nuScenes and FrontCam datasets. To demonstrate their applicability, we use the trained LiDAR tokenizers to extend an image synthesis Transformer model MaskGIT into multimodal image-LiDAR synthesis. The model shows promising results and application in tasks such as LiDAR-conditioned image synthesis
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