Ramamoorthi, Ravi

NeRF: representing scenes as neural radiance fields for view synthesis

Mildenhall, B., Srinivasan, P. P., Tancik, M., Barron, J. T., Ramamoorthi, R., & Ng, R. (2022) · Communications of the ACM

3D Shape Modeling and AnalysisComputer Graphics and Visualization Techniques

Cited by 6,852

NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis

Mildenhall, B., Srinivasan, P. P., Tancik, M., Barron, J. T., Ramamoorthi, R., & Ng, R. (2020) · Lecture Notes in Computer Science

3D Shape Modeling and AnalysisComputer Graphics and Visualization Techniques

Cited by 5,351

Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Tancik, M., Srinivasan, P. P., Mildenhall, B., Fridovich-Keil, S., Raghavan, N., Singhal, U., Ramamoorthi, R., Barron, J. T., & Ng, R. (2020) · arXiv

Neural Networks and ApplicationsStochastic Gradient Optimization Techniques

Cited by 1,459

Deep Stereo Using Adaptive Thin Volume Representation With Uncertainty Awareness

Cheng, S., Xu, Z., Zhu, S., Li, Z., Li, L. E., Ramamoorthi, R., & Su, H. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Vision and Imaging3D Shape Modeling and Analysis

Cited by 385

City Forensics: Using Visual Elements to Predict Non-Visual City Attributes

Arietta, S. M., Efros, A. A., Ramamoorthi, R., & Agrawala, M. (2014) · IEEE Transactions on Visualization and Computer Graphics

Urban Design and Spatial AnalysisData Visualization and Analytics

Cited by 139