What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Operating system
His main research concerns Artificial intelligence, Computer vision, Iterative reconstruction, Pose and Computer graphics.
His Artificial intelligence research incorporates elements of Machine learning and Pattern recognition.
Marc Pollefeys frequently studies issues relating to Metric and Computer vision.
His study focuses on the intersection of Iterative reconstruction and fields such as Pixel with connections in the field of Stereopsis, Rendering and Image resolution.
His work deals with themes such as Inertial measurement unit and Image retrieval, which intersect with Pose.
His work in the fields of Computer graphics, such as Graphics and Stereo cameras, intersects with other areas such as Set.
His most cited work include:
- Visual Modeling with a Hand-Held Camera (848 citations)
- Self-calibration and metric reconstruction in spite of varying and unknown internal camera parameters (712 citations)
- Detailed Real-Time Urban 3D Reconstruction from Video (650 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Artificial intelligence, Computer vision, 3D reconstruction, Pattern recognition and Pose.
His research ties Computer graphics and Artificial intelligence together.
Marc Pollefeys is interested in Rendering, which is a branch of Computer graphics.
As part of his studies on Computer vision, Marc Pollefeys frequently links adjacent subjects like Visualization.
His 3D reconstruction research is multidisciplinary, incorporating perspectives in Algorithm and Surface reconstruction.
He usually deals with Pattern recognition and limits it to topics linked to Deep learning and Convolutional neural network.
He most often published in these fields:
- Artificial intelligence (90.44%)
- Computer vision (71.16%)
- 3D reconstruction (19.28%)
What were the highlights of his more recent work (between 2019-2021)?
- Artificial intelligence (90.44%)
- Computer vision (71.16%)
- Pattern recognition (13.32%)
In recent papers he was focusing on the following fields of study:
Marc Pollefeys spends much of his time researching Artificial intelligence, Computer vision, Pattern recognition, Pose and Feature.
His is doing research in Artificial neural network, Robustness, Representation, Feature extraction and Point cloud, both of which are found in Artificial intelligence.
Computer vision and Pipeline are frequently intertwined in his study.
His study in Pattern recognition is interdisciplinary in nature, drawing from both 3D reconstruction, Key and Encoding.
His Pose research includes elements of Leverage, Sliding window protocol, Feature learning, Odometry and Visualization.
His Feature research includes themes of Matching, Mixed reality and Data mining.
Between 2019 and 2021, his most popular works were:
- Convolutional Occupancy Networks (58 citations)
- DIST: Rendering Deep Implicit Signed Distance Function With Differentiable Sphere Tracing (45 citations)
- SurfelMeshing: Online Surfel-Based Mesh Reconstruction (16 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Operating system
Marc Pollefeys mainly investigates Artificial intelligence, Computer vision, Pose, Robustness and Feature.
In Artificial intelligence, Marc Pollefeys works on issues like Key, which are connected to Image retrieval.
Marc Pollefeys integrates several fields in his works, including Computer vision and Inertial frame of reference.
His Pose study combines topics from a wide range of disciplines, such as Visualization and Data mining.
The study incorporates disciplines such as Implicit function, Tracing, Graphics, Signed distance function and Rendering in addition to Robustness.
His Feature research is multidisciplinary, incorporating elements of Mixed reality, Upload, Structure from motion, Cloud computing and Server.
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