Search Results for author:
Found 5 papers, 1 papers with code
Cascaded and Generalizable Neural Radiance Fields for Fast View Synthesis
Moreover, our method can leverage a denser set of reference images of a single scene to produce accurate novel views without relying on additional explicit representations and still maintains the high-speed rendering of the pre-trained model.
Free-Viewpoint RGB-D Human Performance Capture and Rendering
While prior work has shown impressive performance capture results in laboratory settings, it is non-trivial to achieve casual free-viewpoint human capture and rendering for unseen identities with high fidelity, especially for facial expressions, hands, and clothes.
Sequential View Synthesis with Transformer
This paper addresses the problem of novel view synthesis by means of neural rendering, where we are interested in predicting the novel view at an arbitrary camera pose based on a given set of input images from other viewpoints.
Guiding Monocular Depth Estimation Using Depth-Attention Volume
Recovering the scene depth from a single image is an ill-posed problem that requires additional priors, often referred to as monocular depth cues, to disambiguate different 3D interpretations.
Predicting Novel Views Using Generative Adversarial Query Network
The problem of predicting a novel view of the scene using an arbitrary number of observations is a challenging problem for computers as well as for humans.
