Position-Based Simulation Methods in Computer Graphics
By Jan Bender, Matthias Müller, Miles Macklin. 2015
126 citations recorded by the source corpus.
Subfields: Building and Construction, Computer Vision and Pattern Recognition, Control and Systems Engineering
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- Josh Tenenbaum
- Daniel L. K. Yamins
- Li Fei-Fei
- Luc Van Gool
- Cordelia Schmid
- Chengxu Zhuang
- Trevor Darrell
- Jitendra Malik
In Control and Systems Engineering
- Hang Yin
- Danica Kragic
- Josh Tenenbaum
- Anastasia Varava
- Daniel L. K. Yamins
- Damian Mrowca
- Nick Haber
- Li Fei-Fei
Citations in the corpus
- Flexible Neural Representation for Physics Prediction (2018, methodology): “Our particle-based object representation also draws inspiration from recent work on (non-neural-network) physics simulation, in particular the NVIDIA FleX engine [31, 6].”
- Modeling, learning, perception, and control methods for deformable object manipulation (2021, background): “PHYSICS-BASED MODELING OF DEFORMABLE OBJECTS Modeling and simulating dynamics of deformable objects relies most often on geometric representations using particles or meshes (11, 12).”