Interactive Character Animation Using Simulated Physics: A State‐of‐the‐Art Review

By Thomas Geijtenbeek, Nicolas Pronost. 2012

139 citations recorded by the source corpus.

Subfields: Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition, Control and Systems Engineering, Generative Models

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Graphics and Computer-Aided Design

1. Greg Turk
2. Michiel van de Panne
3. C. Karen Liu
4. Glen Berseth
5. KangKang Yin
6. Xue Bin Peng
7. Nicolas Manfred Otto Heess
8. Wenhao Yu

In Computer Vision and Pattern Recognition

1. Sergey Levine
2. Luc Van Gool
3. Jitendra Malik
4. Pieter Abbeel
5. Trevor Darrell
6. Dacheng Tao
7. Xiaogang Wang
8. Li Fei-Fei

In Control and Systems Engineering

1. Sergey Levine
2. Pieter Abbeel
3. Nicolas Manfred Otto Heess
4. Xue Bin Peng
5. Josh Merel
6. Yuval Tassa
7. David Silver
8. Chelsea Finn

In Generative Models

1. S. M. Ali Eslami
2. David Silver
3. Greg Turk
4. Michiel van de Panne
5. Josh Merel
6. Tom Erez
7. Yuval Tassa
8. Ziyun Wang

Citations in the corpus

• Emergence of Locomotion Behaviours in Rich Environments (2017, background): “Physics-based character animation is a long-standing and active field that has produced a large body of work with impressive results endowing simulated characters with locomotion and other movement skills (see [23] for a review).”
• Learning symmetric and low-energy locomotion (2018, methodology): “Existing algorithms in character control usually require breaking the motion into more manageable parts or using motion data in order to generate natural-looking results [Geijtenbeek and Pronost 2012].”
• DeepLoco (2017, methodology): “Physics-based Character Control: A recent survey on physics-based character animation and control techniques provides a comprehensive overview of work in this area [Geijtenbeek and Pronost 2012].”