Generative novel view synthesis with 3d-aware diffusion models
We present a diffusion-based model for 3D-aware generative novel view synthesis from as
few as a single input image. Our model samples from the distribution of possible renderings …
few as a single input image. Our model samples from the distribution of possible renderings …
Neural fields in visual computing and beyond
Recent advances in machine learning have led to increased interest in solving visual
computing problems using methods that employ coordinate‐based neural networks. These …
computing problems using methods that employ coordinate‐based neural networks. These …
Att3d: Amortized text-to-3d object synthesis
Text-to-3D modelling has seen exciting progress by combining generative text-to-image
models with image-to-3D methods like Neural Radiance Fields. DreamFusion recently …
models with image-to-3D methods like Neural Radiance Fields. DreamFusion recently …
Advances in neural rendering
Synthesizing photo‐realistic images and videos is at the heart of computer graphics and has
been the focus of decades of research. Traditionally, synthetic images of a scene are …
been the focus of decades of research. Traditionally, synthetic images of a scene are …
pi-gan: Periodic implicit generative adversarial networks for 3d-aware image synthesis
ER Chan, M Monteiro, P Kellnhofer… - Proceedings of the …, 2021 - openaccess.thecvf.com
We have witnessed rapid progress on 3D-aware image synthesis, leveraging recent
advances in generative visual models and neural rendering. Existing approaches however …
advances in generative visual models and neural rendering. Existing approaches however …
Learning continuous image representation with local implicit image function
How to represent an image? While the visual world is presented in a continuous manner,
machines store and see the images in a discrete way with 2D arrays of pixels. In this paper …
machines store and see the images in a discrete way with 2D arrays of pixels. In this paper …
Light field networks: Neural scene representations with single-evaluation rendering
Inferring representations of 3D scenes from 2D observations is a fundamental problem of
computer graphics, computer vision, and artificial intelligence. Emerging 3D-structured …
computer graphics, computer vision, and artificial intelligence. Emerging 3D-structured …
Neat: Neural attention fields for end-to-end autonomous driving
Efficient reasoning about the semantic, spatial, and temporal structure of a scene is a crucial
prerequisite for autonomous driving. We present NEural ATtention fields (NEAT), a novel …
prerequisite for autonomous driving. We present NEural ATtention fields (NEAT), a novel …
Eagles: Efficient accelerated 3d gaussians with lightweight encodings
Abstract Recently, 3D Gaussian splatting (3D-GS) has gained popularity in novel-view
scene synthesis. It addresses the challenges of lengthy training times and slow rendering …
scene synthesis. It addresses the challenges of lengthy training times and slow rendering …
Bacon: Band-limited coordinate networks for multiscale scene representation
Coordinate-based networks have emerged as a powerful tool for 3D representation and
scene reconstruction. These networks are trained to map continuous input coordinates to the …
scene reconstruction. These networks are trained to map continuous input coordinates to the …