Search Results for author:
Found 11 papers, 10 papers with code
Shape, Pose, and Appearance from a Single Image via Bootstrapped Radiance Field Inversion
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.
Safe Deep Reinforcement Learning for Multi-Agent Systems with Continuous Action Spaces
Multi-agent control problems constitute an interesting area of application for deep reinforcement learning models with continuous action spaces.
Vanishing Curvature and the Power of Adaptive Methods in Randomly Initialized Deep Networks
This paper revisits the so-called vanishing gradient phenomenon, which commonly occurs in deep randomly initialized neural networks.
Learning Generative Models of Textured 3D Meshes from Real-World Images
Recent advances in differentiable rendering have sparked an interest in learning generative models of textured 3D meshes from image collections.
Convolutional Generation of Textured 3D Meshes
A key contribution of our work is the encoding of the mesh and texture as 2D representations, which are semantically aligned and can be easily modeled by a 2D convolutional GAN.
Hierarchical Image Classification using Entailment Cone Embeddings
Image classification has been studied extensively, but there has been limited work in using unconventional, external guidance other than traditional image-label pairs for training.
Controlling Style and Semantics in Weakly-Supervised Image Generation
We propose a weakly-supervised approach for conditional image generation of complex scenes where a user has fine control over objects appearing in the scene.
Modeling Human Motion with Quaternion-based Neural Networks
Previous work on predicting or generating 3D human pose sequences regresses either joint rotations or joint positions.
3D human pose estimation in video with temporal convolutions and semi-supervised training
We start with predicted 2D keypoints for unlabeled video, then estimate 3D poses and finally back-project to the input 2D keypoints.
Ranked #13 on
Weakly-supervised 3D Human Pose Estimation
on Human3.6M
(Number of Frames Per View metric)
QuaterNet: A Quaternion-based Recurrent Model for Human Motion
Deep learning for predicting or generating 3D human pose sequences is an active research area.
Quootstrap: Scalable Unsupervised Extraction of Quotation-Speaker Pairs from Large News Corpora via Bootstrapping
We propose Quootstrap, a method for extracting quotations, as well as the names of the speakers who uttered them, from large news corpora.
