Search Results for author:
Found 6 papers, 4 papers with code
Omnivore: A Single Model for Many Visual Modalities
Prior work has studied different visual modalities in isolation and developed separate architectures for recognition of images, videos, and 3D data.
Ranked #1 on
Scene Recognition
on SUN-RGBD
(using extra training data)
Recognizing Scenes from Novel Viewpoints
Humans can perceive scenes in 3D from a handful of 2D views.
PyTorchVideo: A Deep Learning Library for Video Understanding
We introduce PyTorchVideo, an open-source deep-learning library that provides a rich set of modular, efficient, and reproducible components for a variety of video understanding tasks, including classification, detection, self-supervised learning, and low-level processing.
Worldsheet: Wrapping the World in a 3D Sheet for View Synthesis from a Single Image
We present Worldsheet, a method for novel view synthesis using just a single RGB image as input.
Accelerating 3D Deep Learning with PyTorch3D
We address these challenges by introducing PyTorch3D, a library of modular, efficient, and differentiable operators for 3D deep learning.
C3DPO: Canonical 3D Pose Networks for Non-Rigid Structure From Motion
We propose C3DPO, a method for extracting 3D models of deformable objects from 2D keypoint annotations in unconstrained images.
