ENHANCED NOVEL VIEW SYTHESIS VIA DEEP LEARNING-BASED 3D GAUSSIAN SPLATTING / (Record no. 613799)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 01506nam a22001577a 4500 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 629.8 |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Zabeeh Ullah Noor |
| 245 ## - TITLE STATEMENT | |
| Title | ENHANCED NOVEL VIEW SYTHESIS VIA DEEP LEARNING-BASED 3D GAUSSIAN SPLATTING / |
| 264 ## - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
| Place of production, publication, distribution, manufacture | Islamabad: |
| Name of producer, publisher, distributor, manufacturer | SMME- NUST. |
| Date of production, publication, distribution, manufacture, or copyright notice | 2024. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 83p. ; |
| Other physical details | Soft Copy, |
| Dimensions | 30cm. |
| 500 ## - GENERAL NOTE | |
| General note | 3D Gaussian Splatting (3DGS) has emerged as a breakthrough in explicit radiance<br/>fields and computer graphics which has enabled precise scene representation, real<br/>time rendering, and efficient novel view synthesis. This paper explores the evolution<br/>of 3D rendering and recent advancements in 3DGS, with a particular focus on<br/>different techniques for synthesizing novel views with the incorporation of deep<br/>learning architectures especially transformers. To enhance scene quality, this<br/>research investigates the integration of monocular depth information during<br/>rendering and refines the loss function to improve reconstruction accuracy. By<br/>incorporating depth information our method enhances geometric details by<br/>capturing intricate details and reduction of artifacts. The findings contribute to the<br/>reconstruction of 3D scene with high fidelity, offering insights to optimize Gaussian<br/>Splatting technique for more efficient and realistic 3D rendering applications. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | MS Robotics and Intelligent Machine Engineering |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Dr Sara Baber |
| 856 ## - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | <a href="http://10.250.8.41:8080/xmlui/handle/123456789/52946">http://10.250.8.41:8080/xmlui/handle/123456789/52946</a> |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | |
| Koha item type | Thesis |
No items available.