Gaussians as Supervision for Joint Physical Parameter Estimation and Appearance Reconstruction of Elastic Objects

Recovering the appearance and physical parameters of elastic objects from multi-view video is essential for many applications that require simulation of the real world. Past methods for this task have provided accurate results in recovering physical properties; however, their re- liance on Neural Radiance Fields (NeRFs) for novel view synthesis...

Procedural Tree Generation: How to efficiently predict branching structures from foliage?

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...

Procedural Tree Generation: Inverse Modelling of 2D Trees using Graph Neural Networks

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...

Procedural Tree Generation: Compressing 3D tree for faster rendering

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...

Isolating a Tree’s Skeleton using a 3-Dimensional Reconstruction

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...

Neural Radiance Field (NeRF) as a Rendering Primitive: StreamNeRF - Adapting a NeRF Model for Progressive Decoding

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...

Depth Light Field Training (DeLFT): NeRF as a rendering primitive

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...

Using K-Means clustering to export a NeRF for faster rendering in CG applications while preserving view-dependent appearance

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...

Non-Photorealistic Novel View Synthesis Using Radiance Fields

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...

How can hyperspectral projection enhance chromostereoscopic perception?

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...

The Perfect Picture: Optimising Chromostereoscopic Images for Desired Depth and Colour

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...

Real-Time Chromostereopsis for Arbitrary Three-Dimensional Scenes

Chromostereopsis is a visual illusion that can produce perceived 3D images through an effect caused by how humans see different wavelengths. ChromaDepth glasses may be worn to exploit this phenomenon and amplify the effect. Relative to other forms of stereoscopy, chromostereoscopy is lesser-known and has seen fewer applications. This paper seeks...

Simulating the ChromaDepth Eect for CMYK-based Print Media

Chromastereoscopy makes use of special glasses to make its wearer see two slightly different images, one for each eye. With a properly created image this results in perceived depth. It does this by bending light dependent on its wavelength and in the opposite direction for each eye. When a ChromaDepth image is properly created most viewers...

Using Chromostereopsis to Enhance Depth Perception in Photos by changing the Hue

The following paper explores the use of chromostereopsis for the purpose of enhancing the perceived depth in photos. Contrary to previous work, this is achieved by using a continuous depth map as input and creating a natural-looking photo with enhanced depth even when viewed without any type of three dimension technology. This is the first...