Gaurav Shrivastava I am a final year PhD student at University of Maryland, College Park advised by Prof. Abhinav Shrivastava. My research focuses on the intersection of Machine Learning and Computer Vision. Specifically, my work encompasses Diffusion, Video Generation, Computational Photography, and Gaussian Process models. |
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Video Prediction by Modeling Videos as Continuous Multi-Dimensional Processes
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Coming Soon! |
Video Decomposition Prior: Editing Videos Layer by Layer
PDF /Project Page
Coming Soon! |
Video Dynamics Prior: An Internal Learning Approach for Robust Video Enhancements @inproceedings{ shrivastava2023video, title={Video Dynamics Prior: An Internal Learning Approach for Robust Video Enhancements}, author={Gaurav Shrivastava and Ser-Nam Lim and Abhinav Shrivastava}, booktitle={Thirty-seventh Conference on Neural Information Processing Systems}, year={2023}, url={https://openreview.net/forum?id=CCq73CGMyV} } |
Hierarchical Video Prediction using Relational Layouts for Human-object Interactions @InProceedings{Bodla_2021_CVPR, author = {Bodla, Navaneeth and Shrivastava, Gaurav and Chellappa, Rama and Shrivastava, Abhinav}, title = {Hierarchical Video Prediction Using Relational Layouts for Human-Object Interactions}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, month = {June}, year = {2021}, pages = {12146-12155} } |
Diverse Video Generation using a Gaussian Process Trigger @inproceedings{ shrivastava2021diverse, title={Diverse Video Generation using a Gaussian Process Trigger}, author={Gaurav Shrivastava and Abhinav Shrivastava}, booktitle={International Conference on Learning Representations}, year={2021}, url={https://openreview.net/forum?id=Qm7R_SdqTpT} } |
Learning What Not to Model: Gaussian Process Regression with Negative Constraints
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bibtex
Coming Soon! @techreport{Shrivastava2020negGP, bibtex_show={true}, abbr = {PI-TechReport}, author={Gaurav Shrivastava and Abhinav Shrivastava}, title={Learning What Not to Model: Gaussian Process Regression with Negative Constraints}, type = {Perception and Intelligence Technical Report}, publisher = {Perception and Intelligence Tech Report}, address = {College Park, Maryland, US}, pdf = {gpnc.pdf}, year={2020}} |