Sampling for View Synthesis: From Local Light Field Fusion to Neural Radiance Fields and Beyond
Offered By: BIMSA via YouTube
Course Description
Overview
Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore the evolution of view synthesis techniques in computer graphics and vision through this 50-minute conference talk by Ravi Ramamoorthi at #ICBS2024. Delve into the challenges of capturing and rendering novel views of complex real-world scenes, with applications in AR, VR, and 3D photography. Examine the impact of deep learning on image-based rendering and discover the Local Light Field Fusion algorithm, which enables practical view synthesis from irregularly sampled views. Learn about the extension of plenoptic sampling theory and its implications for efficient view sampling. Investigate recent developments in scene representations, including neural radiance fields, and consider the ongoing importance of sparse view synthesis. Reflect on the potential for prescriptive sampling guidelines in modern image-based rendering algorithms as you gain insights into this cutting-edge field.
Syllabus
Ravi Ramamoorthi: Sampling for View Synthesis: From Local Light Field Fusion to Neural... #ICBS2024
Taught by
BIMSA
Related Courses
3D Art and Audio PipelineUnity via Coursera 3D Transforms in Adobe XD
Coursera Project Network via Coursera Applying Advanced Spark AR Tools and Effects
Meta via edX Introduction to Augmented Reality and ARCore
Google Daydream Impact via Coursera AR for web using JavaScript
Meta via Coursera