465 citations · 4.1k across the 97 of their papers we have counts for
10 papers · 1 filter
VideoGPT: Video Generation using VQ-VAE and Transformers
Wilson Yan, Yunzhi Zhang, Pieter Abbeel +1
We present VideoGPT: a conceptually simple architecture for scaling likelihood based generative modeling to natural videos. VideoGPT uses VQ-VAE that learns downsampled discrete la…
Putting NeRF on a Diet: Semantically Consistent Few-Shot View Synthesis
Ajay Jain, Matthew Tancik, Pieter Abbeel
We present DietNeRF, a 3D neural scene representation estimated from a few images. Neural Radiance Fields (NeRF) learn a continuous volumetric representation of a scene through mul…
Bottleneck Transformers for Visual Recognition
Aravind Srinivas, Tsung-Yi Lin, Niki Parmar +3
We present BoTNet, a conceptually simple yet powerful backbone architecture that incorporates self-attention for multiple computer vision tasks including image classification, obje…
Mutual Information Maximization for Robust Plannable Representations
Yiming Ding, Ignasi Clavera, Pieter Abbeel
Extending the capabilities of robotics to real-world complex, unstructured environments requires the need of developing better perception systems while maintaining low sample compl…
Natural Image Manipulation for Autoregressive Models Using Fisher Scores
Wilson Yan, Jonathan Ho, Pieter Abbeel
Deep autoregressive models are one of the most powerful models that exist today which achieve state-of-the-art bits per dim. However, they lie at a strict disadvantage when it come…
Geometry-Aware Neural Rendering
Josh Tobin, OpenAI Robotics, Pieter Abbeel
Understanding the 3-dimensional structure of the world is a core challenge in computer vision and robotics. Neural rendering approaches learn an implicit 3D model by predicting wha…