Searched for: kellnhofer
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Taklimi, Sam (author)
The objective of this project is to train a model that transforms a tree with its foliage into only its branch structure. This is achieved by employing machine-learning techniques, specifically Generative Adverserial Networks (GANs). By utilizing the proposed method, a predictive model is built that automatically minimizes its own error function...
bachelor thesis 2024
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Mozafari, Erfan (author)
The most established and widely used methods for analysing tree images for tasks such as geometry analysis, segmentation and classification often rely on pixels. In this paper, the applicability of analyzing tree geometry based on a graph representation rather than a pixel-based approach is pursued. To do so, 2D renders of different species of...
bachelor thesis 2024
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Manda, Sebastian (author)
Trees are essential components of both real and digital environments. Therefore, it is important to have 3D models of trees that are of high quality and computationally efficient. One way to achieve this is by compressing a high-quality model using billboard rendering, which involves partitioning the tree into multiple planes to produce a...
bachelor thesis 2024
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Sahay, Shashwat (author)
L-Systems allow for the efficient procedeural generation of trees to be used for rendering in video games and simulations. Currently, however, it is difficult to engineer grammars that mimic the behaviours of real life trees in 3 dimensions. To be able to deduce them, the skeleton of a tree can be used to train a model and generate an L-system...
bachelor thesis 2024
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Lin, Zhi-Yi (author)
Human 3D kinematics estimation involves measuring joint angles and body segment scales to quantify and analyze the mechanics of human movements. It has applications in areas such as injury prevention, disease identification, and sports science. Conventional marker-based motion capture methods are expensive both in terms of financial investment...
master thesis 2023
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Găleşanu, Matei (author)
Neural Radiance Fields (NeRF) and their adaptations are known to be computationally intensive during both the training and the evaluating stages. Despite being the end goal, directly rendering a full-resolution representation of the scene is not necessary and not very practical for scenarios like streamed applications. Our goal is to design a...
bachelor thesis 2023
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Toader, Mihnea (author)
Neural radiance fields (NeRF) based solutions for novel view synthesis can achieve state of the art results. Recent work proposes models that take less time to render, need less training data or take up less space. However, few papers explore the use of NeRFs in classic rendering scenarios such as rasterization, which could contribute to wider...
bachelor thesis 2023
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Groenendijk, Jurre (author)
With the current state-of-the-art research, exporting a NeRF to a mesh has the side effect of having to evaluate a Multi Layer Perceptron at render-time, causing a significant decrease in performance. We have found a way to use K-Means clustering to pre-compute values for this MLP, storing them in multiple octahedron maps for the GPU to fetch...
bachelor thesis 2023
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Szilvásy, Medárd (author)
Radiance fields are a promising alternative to conventional 3D representations in the domain of novel view synthesis, with recent research achieving truly impressive photorealistic view synthesis results. In this paper, we deal with the concept of non-photorealistic rendering in the context of radiance fields, for generating more stylistic...
bachelor thesis 2023
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Warchocki, Jan (author)
In temporal action localization, given an input video, the goal is to predict which actions it contains, where they begin and where they end. Training and testing current state-of-the-art, deep learning models is done assuming access to large amounts of data and computational power. Gathering such data is however a challenging task and access to...
bachelor thesis 2023
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Dămăcuş, Alex (author)
In temporal action localization, given an input video, the goal is to predict the action that is present in the video, along with its temporal boundaries. Several powerful models have been proposed throughout the years, with transformer-based models achieving state-of-the-art performance in the recent months. Although novel models are becoming...
bachelor thesis 2023
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Misterka, Paul (author)
Temporal Action Localization (TAL) is an important problem in computer vision with uses in video surveillance and recommendation, healthcare, entertainment, and human-computer interaction. Being an inherently data-heavy process, TAL has been bound by the availability of computing power, resulting in its slow pace of innovation. This work aims to...
bachelor thesis 2023
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Wang, Yunhan (author)
Temporal Action Localization (TAL) aims to localize the start and end times of actions in untrimmed videos and classify the corresponding action types. TAL plays an important role in understanding video. Existing TAL approaches heavily rely on deep learning and require large-scale data and expensive training processes. Recent advances in...
bachelor thesis 2023
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Oprescu, Teodor (author)
This paper presents an analysis of the data and compute efficiency of the TemporalMaxer deep learning model in the context of temporal action localization (TAL), which involves accurately detecting the start and end times of specific video actions. The study explores the performance and scalability of the TemporalMaxer model under limited...
bachelor thesis 2023
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Hristov, Tsvetomir (author)
Although digital watermarking has been a well-researched topic for the past decades and has seen numerous implementations for relational databases, it still lacks research for non-relational schema-less databases. In this paper, we explore proposed techniques for non-relational database watermarking and introduce an improved technique for NoSQL...
bachelor thesis 2023
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Li, Ruonan (author)
Datasets play an important role in machine learning technology. The quality of a machine learning model is highly dependent on the quality of the training dataset. Datasets are of great economic value and should be viewed as intellectual property. To protect the property rights of machine learning training datasets, we can make use of the...
bachelor thesis 2023
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Maesen, Palle (author)
The media watermarking technique domain has had the last 30 years to develop itself. The non-media side, however, is a way newer sub-domain. [1] The data-gathering process for machine learning algorithms is a tedious and time consuming task. This becomes worse as the scale of these algorithms increases. Thus, protecting the datasets against...
bachelor thesis 2023
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Smitskamp, Gwennan (author)
The need to capture environments and objects in 3 dimensions to produce a high quality digital representation is proving to be useful in many applications in the world, where there is an increasing dependence on digital spaces. Point Clouds are a data type to represent 3D objects and scenes. During the processing of the point cloud data,...
master thesis 2022
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Stroia, Marco (author)
Chromostereopsis is an optical illusion that allows 2D images to simulate depth based on color. For example, red is perceived to be closer than blue, when displayed on a black background. This effect is present because of the slight chromatic aberration caused by the eye lens, and it can be strengthened by the use of ChromaDepth® glasses. This...
bachelor thesis 2022
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Sjerps, Thomas (author)
Chromostereoscopic images encode depth as colour, with the red part of the visible spectrum encoding nearby depths and the blue part encoding far-away depths. However, when encoding a regular image with its depth, the generated colours may not match with the original colours in the image. Following a user study, a technique has been developed...
bachelor thesis 2022
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