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Found 6 papers, 3 papers with code
RUST: Latent Neural Scene Representations from Unposed Imagery
Our main insight is that one can train a Pose Encoder that peeks at the target image and learns a latent pose embedding which is used by the decoder for view synthesis.
Kubric: A scalable dataset generator
Data is the driving force of machine learning, with the amount and quality of training data often being more important for the performance of a system than architecture and training details.
Scene Representation Transformer: Geometry-Free Novel View Synthesis Through Set-Latent Scene Representations
In this work, we propose the Scene Representation Transformer (SRT), a method which processes posed or unposed RGB images of a new area, infers a "set-latent scene representation", and synthesises novel views, all in a single feed-forward pass.
NeSF: Neural Semantic Fields for Generalizable Semantic Segmentation of 3D Scenes
We present NeSF, a method for producing 3D semantic fields from posed RGB images alone.
Self-supervisory Signals for Object Discovery and Detection
In robotic applications, we often face the challenge of discovering new objects while having very little or no labelled training data.
Generating Wikipedia by Summarizing Long Sequences
We show that generating English Wikipedia articles can be approached as a multi- document summarization of source documents.
