15 citations · 49 across the 16 of their papers we have counts for
7 papers · 1 filter
Unsupervised Simultaneous Learning for Camera Re-Localization and Depth Estimation from Video
Shun Taguchi, Noriaki Hirose
We present an unsupervised simultaneous learning framework for the task of monocular camera re-localization and depth estimation from unlabeled video sequences. Monocular camera re…
Depth360: Self-supervised Learning for Monocular Depth Estimation using Learnable Camera Distortion Model
Noriaki Hirose, Kosuke Tahara
Self-supervised monocular depth estimation has been widely investigated to estimate depth images and relative poses from RGB images. This framework is attractive for researchers be…
Variational Monocular Depth Estimation for Reliability Prediction
Noriaki Hirose, Shun Taguchi, Keisuke Kawano +1
Self-supervised learning for monocular depth estimation is widely investigated as an alternative to supervised learning approach, that requires a lot of ground truths. Previous wor…
PLG-IN: Pluggable Geometric Consistency Loss with Wasserstein Distance in Monocular Depth Estimation
Noriaki Hirose, Satoshi Koide, Keisuke Kawano +1
We propose a novel objective for penalizing geometric inconsistencies to improve the depth and pose estimation performance of monocular camera images. Our objective is designed usi…
VUNet: Dynamic Scene View Synthesis for Traversability Estimation using an RGB Camera
Noriaki Hirose, Amir Sadeghian, Fei Xia +2
We present VUNet, a novel view(VU) synthesis method for mobile robots in dynamic environments, and its application to the estimation of future traversability. Our method predicts f…
SoPhie: An Attentive GAN for Predicting Paths Compliant to Social and Physical Constraints
Amir Sadeghian, Vineet Kosaraju, Ali Sadeghian +3
This paper addresses the problem of path prediction for multiple interacting agents in a scene, which is a crucial step for many autonomous platforms such as self-driving cars and…
To Go or Not To Go? A Near Unsupervised Learning Approach For Robot Navigation
Noriaki Hirose, Amir Sadeghian, Patrick Goebel +1
It is important for robots to be able to decide whether they can go through a space or not, as they navigate through a dynamic environment. This capability can help them avoid inju…