no code implementations • NeurIPS 2023 • Gaurav Shrivastava, Ser-Nam Lim, Abhinav Shrivastava
In this paper, we present a novel robust framework for low-level vision tasks, including denoising, object removal, frame interpolation, and super-resolution, that does not require any external training data corpus.
1 code implementation • ICLR 2021 • Gaurav Shrivastava, Abhinav Shrivastava
Our approach, Diverse Video Generator, uses a Gaussian Process (GP) to learn priors on future states given the past and maintains a probability distribution over possible futures given a particular sample.
Ranked #1 on Video Prediction on KTH (Diversity metric)
no code implementations • CVPR 2021 • Navaneeth Bodla, Gaurav Shrivastava, Rama Chellappa, Abhinav Shrivastava
Our work builds on hierarchical video prediction models, which disentangle the video generation process into two stages: predicting a high-level representation, such as pose sequence, and then learning a pose-to-pixels translation model for pixel generation.
no code implementations • 1 Jan 2021 • Gaurav Shrivastava, Harsh Shrivastava, Abhinav Shrivastava
But, what if for an input point '$\bar{\mathbf{x}}$', we want to constrain the GP to avoid a target regression value '$\bar{y}(\bar{\mathbf{x}})$' (a negative datapair)?