Search Results for author:
Found 8 papers, 3 papers with code
Consistent Multimodal Generation via A Unified GAN Framework
We investigate how to generate multimodal image outputs, such as RGB, depth, and surface normals, with a single generative model.
Socially Compliant Navigation Dataset (SCAND): A Large-Scale Dataset of Demonstrations for Social Navigation
Social navigation is the capability of an autonomous agent, such as a robot, to navigate in a 'socially compliant' manner in the presence of other intelligent agents such as humans.
Accurately Solving Rod Dynamics with Graph Learning
In this contribution, we introduce a novel method to accelerate iterative solvers for rod dynamics with graph networks (GNs) by predicting the initial guesses to reduce the number of iterations.
Unsupervised Monocular Depth and Ego-motion Learning with Structure and Semantics
We present an approach which takes advantage of both structure and semantics for unsupervised monocular learning of depth and ego-motion.
Future Segmentation Using 3D Structure
Predicting the future to anticipate the outcome of events and actions is a critical attribute of autonomous agents; particularly for agents which must rely heavily on real time visual data for decision making.
Depth Prediction Without the Sensors: Leveraging Structure for Unsupervised Learning from Monocular Videos
Models and examples built with TensorFlow
Ranked #10 on
Unsupervised Monocular Depth Estimation
on Cityscapes
Parsing Geometry Using Structure-Aware Shape Templates
Real-life man-made objects often exhibit strong and easily-identifiable structure, as a direct result of their design or their intended functionality.
FPNN: Field Probing Neural Networks for 3D Data
Each field probing filter is a set of probing points --- sensors that perceive the space.
Ranked #5 on
3D Object Recognition
on ModelNet40
