In-context learningx2013the ability to configure a model's
behavior with...
The core problem in zero-shot open vocabulary detection is how to align
...
Self-supervised methods have achieved remarkable success in transfer
lea...
The promise of self-supervised learning (SSL) is to leverage large amoun...
General perception systems such as Perceivers can process arbitrary
moda...
Much of the recent progress in 3D vision has been driven by the developm...
Neural radiance fields (NeRF) methods have demonstrated impressive novel...
Videos are a rich source of multi-modal supervision. In this work, we le...
In this work we target the problem of estimating accurately localised
co...
The objective of this work is to learn a compact embedding of a set of
d...
The objective of this paper is to be able to separate a video into its
n...
We tackle the problem of object discovery, where objects are segmented f...
We address the problem of finding reliable dense correspondences between...
The objective of this paper is to learn a compact representation of imag...
This paper proposes a new algorithmic framework,predictor-verifier
train...
We tackle the task of semantic alignment where the goal is to compute de...
In this paper our objectives are, first, networks that can embed audio a...
We consider the question: what can be learnt by looking at and listening...
We address the problem of determining correspondences between two images...
We consider the task of lossy compression of high-dimensional vectors th...