Recent years have witnessed significant progress in example-based texture synthesis algorithms. Given an example texture, these methods produce a larger texture that is tailored …
We introduce a novel sequential modeling approach which enables learning a Large Vision Model (LVM) without making use of any linguistic data. To do this we define a common …
Z Li, R Tucker, N Snavely… - Proceedings of the IEEE …, 2024 - openaccess.thecvf.com
We present an approach to modeling an image-space prior on scene motion. Our prior is learned from a collection of motion trajectories extracted from real video sequences …
We present a video generation model that accurately reproduces object motion, changes in camera viewpoint, and new content that arises over time. Existing video generation methods …
We study the problem of video-to-video synthesis, whose goal is to learn a mapping function from an input source video (eg, a sequence of semantic segmentation masks) to an output …
We present PhysGen, a novel image-to-video generation method that converts a single image and an input condition (eg., force and torque applied to an object in the image) to …
T Xue, J Wu, K Bouman… - Advances in neural …, 2016 - proceedings.neurips.cc
We study the problem of synthesizing a number of likely future frames from a single input image. In contrast to traditional methods, which have tackled this problem in a deterministic …
We introduce the problem of perpetual view generation-long-range generation of novel views corresponding to an arbitrarily long camera trajectory given a single image. This is a …
JZ Kolter, G Manek - Advances in neural information …, 2019 - proceedings.neurips.cc
Deep networks are commonly used to model dynamical systems, predicting how the state of a system will evolve over time (either autonomously or in response to control inputs) …