What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Computer graphics
Matthias Nießner focuses on Artificial intelligence, Computer vision, Computer graphics, RGB color model and Face.
His research investigates the connection with Artificial intelligence and areas like State which intersect with concerns in Computing Methodologies.
His work on Tracking and Segmentation as part of general Computer vision research is often related to Matching and Scale, thus linking different fields of science.
The Computer graphics study combines topics in areas such as Depth map and View synthesis, Rendering.
Matthias Nießner undertakes multidisciplinary investigations into RGB color model and Context in his work.
His Face study combines topics in areas such as Monocular and Facial expression.
His most cited work include:
- Real-time 3D reconstruction at scale using voxel hashing (566 citations)
- ScanNet: Richly-annotated 3D Reconstructions of Indoor Scenes (461 citations)
- BundleFusion: real-time globally consistent 3D reconstruction using on-the-fly surface re-integration (333 citations)
What are the main themes of his work throughout his whole career to date?
Matthias Nießner mostly deals with Artificial intelligence, Computer vision, RGB color model, Computer graphics and Rendering.
His research investigates the link between Artificial intelligence and topics such as Pattern recognition that cross with problems in Margin.
His Computer vision research includes elements of Facial expression and Benchmark.
The study incorporates disciplines such as Tracking and Segmentation in addition to RGB color model.
His work investigates the relationship between Computer graphics and topics such as View synthesis that intersect with problems in Leverage.
Matthias Nießner studied Rendering and Subdivision surface that intersect with Tessellation.
He most often published in these fields:
- Artificial intelligence (75.19%)
- Computer vision (60.15%)
- RGB color model (34.59%)
What were the highlights of his more recent work (between 2019-2021)?
- Artificial intelligence (75.19%)
- Computer vision (60.15%)
- RGB color model (34.59%)
In recent papers he was focusing on the following fields of study:
Matthias Nießner spends much of his time researching Artificial intelligence, Computer vision, RGB color model, Rendering and Object.
In Artificial intelligence, Matthias Nießner works on issues like Pattern recognition, which are connected to Transfer of learning.
His study in the field of Real image and Contrast also crosses realms of Key and CAD.
His RGB color model research incorporates elements of Tracking and Virtual reality.
His research integrates issues of Image synthesis and Computer graphics in his study of Rendering.
His Object study incorporates themes from Contrast and Task.
Between 2019 and 2021, his most popular works were:
- State of the Art on Neural Rendering (54 citations)
- Local Implicit Grid Representations for 3D Scenes (31 citations)
- Image-guided Neural Object Rendering (17 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Machine learning
His primary areas of investigation include Artificial intelligence, Computer vision, Rendering, Computer graphics and Segmentation.
Matthias Nießner combines subjects such as Polygon mesh and Pattern recognition with his study of Artificial intelligence.
His work on Object and RGB color model as part of general Computer vision study is frequently linked to Key and CAD, bridging the gap between disciplines.
Matthias Nießner has included themes like Artificial neural network and Digital reproduction in his RGB color model study.
His Computer graphics research focuses on subjects like Metaverse, which are linked to Image synthesis.
His Segmentation study which covers Point cloud that intersects with Information retrieval and Point.
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