58 citations · 72 across the 5 of their papers we have counts for
4 papers · 1 filter
Unsupervised Monocular Depth Learning in Dynamic Scenes
Hanhan Li, Ariel Gordon, Hang Zhao +2
We present a method for jointly training the estimation of depth, ego-motion, and a dense 3D translation field of objects relative to the scene, with monocular photometric consiste…
Adversarially Robust Frame Sampling with Bounded Irregularities
Hanhan Li, Pin Wang
In recent years, video analysis tools for automatically extracting meaningful information from videos are widely studied and deployed. Because most of them use deep neural networks…
EnsembleNet: End-to-End Optimization of Multi-headed Models
Hanhan Li, Joe Yue-Hei Ng, Paul Natsev
Ensembling is a universally useful approach to boost the performance of machine learning models. However, individual models in an ensemble were traditionally trained independently…
Depth from Videos in the Wild: Unsupervised Monocular Depth Learning from Unknown Cameras
Ariel Gordon, Hanhan Li, Rico Jonschkowski +1
We present a novel method for simultaneous learning of depth, egomotion, object motion, and camera intrinsics from monocular videos, using only consistency across neighboring video…