A comprehensive survey on AR-enabled local collaboration

Recent advances in graphics hardware have enabled ray tracing to produce high-quality ambient occlusion (AO) in real-time, which is not plagued by the artifacts typically found in real-time screen-space approaches. However, the high computational cost of ray tracing remains a significant hurdle for low-power devices like standalone VR headsets or smartphones. To address this challenge, inspired by point-based global illumination and texture-space split rendering, we propose point-based split ambient occlusion (PSAO), a novel split-rendering system that streams points sparsely from server to client. PSAO first evenly distributes points across the scene, and then subsequently only transmits points that changed more than a given threshold, using an efficient hash grid to blend neighboring points for the final compositing pass on the client. PSAO outperforms recent texture-space shading approaches in terms of quality and required network bit rate, while demonstrating performance similar to commonly used lower-quality screen-space approaches. Our point-based split rendering representation lends itself to highly compressible signals such as AO and is scalable towards quality or bandwidth requirements by adjusting the number of points in the scene. CCS Concepts • Computing methodologies → Rendering; † The work was primarily done during an internship at Meta.

PSAO: Point-Based Split Rendering for Ambient Occlusion

We present a generalized decoupled and object space shading system. This system includes a new layer material system, a dynamic hierarchical sparse shade space allocation system, a GPU shade work dispatcher, and a multi-frame shade work distribution system. Together, these new systems create a generalized solution to decoupled shading, solving both the visibility problem, where shading samples which are not visible are shaded; the overshading and under shading problem, where parts of the scene are shaded at higher or lower number of samples than needed; and the shade allocation problem, where shade samples must be efﬁciently stored in GPU memory. The generalized decoupled shading system introduced shades and stores only the samples which are actually needed for the rendering a frame, with minimal overshading and no undershading. It does so with minimal overhead, and overall performance is competitive with other rendering techniques on a modern GPU.

Generalized Decoupled and Object Space Shading System

We present an extension of the existing CoNavigator collaboration system that allows for persistence of in-person collaboration sessions through a digitally projected overlay and camera system. This augmented reality environment allows participants in a CoNavigator session to resume from a previous session without having to laboriously recreate the physical state of the space manually. By combining features traditionally found only in digital space with the intuitive nature of a tactile physical environment, we hope to produce a tool that builds on the work of CoNavigator and lowers barriers to adoption while increasing efficacy.

Extending CoNavigator into a Collaborative Digital Space

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Mark Jarzynski

Author Tools

Chat about Author

Papers

Generalized Decoupled and Object Space Shading System

Extending CoNavigator into a Collaborative Digital Space