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Found 9 papers, 3 papers with code
Gemma 3 Technical Report
We introduce Gemma 3, a multimodal addition to the Gemma family of lightweight open models, ranging in scale from 1 to 27 billion parameters.
Scaling 4D Representations
Scaling has not yet been convincingly demonstrated for pure self-supervised learning from video.
Moving Off-the-Grid: Scene-Grounded Video Representations
By using a combination of cross-attention and positional embeddings we disentangle the representation structure and image structure.
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.
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.
