Neural Radiance Fields (NeRF) coupled with GANs represent a promising direction in the area of 3D reconstruction from a single view, owing to their ability to efficiently model arbitrary topologies.
With this formulation, we train a single multi-task Transformer for 18 RLBench tasks (with 249 variations) and 7 real-world tasks (with 18 variations) from just a few demonstrations per task.
We launch EVA, a vision-centric foundation model to explore the limits of visual representation at scale using only publicly accessible data.
Ranked #1 on Object Detection on LVIS v1.0 val (using extra training data)
In this work, we present a conceptually simple and effective method to train a strong bilingual/multilingual multimodal representation model.
A common approach for knowledge-intensive tasks is to employ a retrieve-then-read pipeline that first retrieves a handful of relevant contextual documents from an external corpus such as Wikipedia and then predicts an answer conditioned on the retrieved documents.
To this end, we compute a tightly-bounded approximation of the solution of an integral appearing in LTCs' dynamics, that has had no known closed-form solution so far.
Ranked #29 on Sentiment Analysis on IMDb
Autonomous agents have made great strides in specialist domains like Atari games and Go.