15 citations · 49 across the 16 of their papers we have counts for
16 papers
ViNT: A Foundation Model for Visual Navigation
Dhruv Shah, Ajay Sridhar, Nitish Dashora +4
General-purpose pre-trained models ("foundation models") have enabled practitioners to produce generalizable solutions for individual machine learning problems with datasets that a…
SACSoN: Scalable Autonomous Control for Social Navigation
Noriaki Hirose, Dhruv Shah, Ajay Sridhar +1
Machine learning provides a powerful tool for building socially compliant robotic systems that go beyond simple predictive models of human behavior. By observing and understanding…
ExAug: Robot-Conditioned Navigation Policies via Geometric Experience Augmentation
Noriaki Hirose, Dhruv Shah, Ajay Sridhar +1
Machine learning techniques rely on large and diverse datasets for generalization. Computer vision, natural language processing, and other applications can often reuse public datas…
GNM: A General Navigation Model to Drive Any Robot
Dhruv Shah, Ajay Sridhar, Arjun Bhorkar +2
Learning provides a powerful tool for vision-based navigation, but the capabilities of learning-based policies are constrained by limited training data. If we could combine data fr…
Spatio-Temporal Graph Localization Networks for Image-based Navigation
Takahiro Niwa, Shun Taguchi, Noriaki Hirose
Localization in topological maps is essential for image-based navigation using an RGB camera. Localization using only one camera can be challenging in medium-to-large-sized environ…
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…
Ex-DoF: Expansion of Action Degree-of-Freedom with Virtual Camera Rotation for Omnidirectional Image
Kosuke Tahara, Noriaki Hirose
Inter-robot transfer of training data is a little explored topic in learning- and vision-based robot control. Here we propose a transfer method from a robot with a lower Degree-of-…
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…
Probabilistic Visual Navigation with Bidirectional Image Prediction
Noriaki Hirose, Shun Taguchi, Fei Xia +4
Humans can robustly follow a visual trajectory defined by a sequence of images (i.e. a video) regardless of substantial changes in the environment or the presence of obstacles. We…
Deep Visual MPC-Policy Learning for Navigation
Noriaki Hirose, Fei Xia, Roberto Martin-Martin +2
Humans can routinely follow a trajectory defined by a list of images/landmarks. However, traditional robot navigation methods require accurate mapping of the environment, localizat…
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…
GONet: A Semi-Supervised Deep Learning Approach For Traversability Estimation
Noriaki Hirose, Amir Sadeghian, Marynel Vázquez +2
We present semi-supervised deep learning approaches for traversability estimation from fisheye images. Our method, GONet, and the proposed extensions leverage Generative Adversaria…
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…