activity
20182022
most citedTartanVO: A Generalizable Learning-based VO

6 citations · 9 across the 6 of their papers we have counts for

collaborators

13 papers

cs.RO20221 cited

TartanDrive: A Large-Scale Dataset for Learning Off-Road Dynamics Models

Samuel Triest, Matthew Sivaprakasam, Sean J. Wang +3

We present TartanDrive, a large scale dataset for learning dynamics models for off-road driving. We collected a dataset of roughly 200,000 off-road driving interactions on a modifi…

cs.RO2022

COMPASS: Contrastive Multimodal Pretraining for Autonomous Systems

Shuang Ma, Sai Vemprala, Wenshan Wang +4

Learning representations that generalize across tasks and domains is challenging yet necessary for autonomous systems. Although task-driven approaches are appealing, designing mode…

cs.RO2021

VDB-EDT: An Efficient Euclidean Distance Transform Algorithm Based on VDB Data Structure

Delong Zhu, Chaoqun Wang, Wenshan Wang +3

This paper presents a fundamental algorithm, called VDB-EDT, for Euclidean distance transform (EDT) based on the VDB data structure. The algorithm executes on grid maps and generat…

cs.CV20211 cited

ORStereo: Occlusion-Aware Recurrent Stereo Matching for 4K-Resolution Images

Yaoyu Hu, Wenshan Wang, Huai Yu +2

Stereo reconstruction models trained on small images do not generalize well to high-resolution data. Training a model on high-resolution image size faces difficulties of data avail…

cs.CV20206 cited

TartanVO: A Generalizable Learning-based VO

Wenshan Wang, Yaoyu Hu, Sebastian Scherer

We present the first learning-based visual odometry (VO) model, which generalizes to multiple datasets and real-world scenarios and outperforms geometry-based methods in challengin…

cs.CV2020

Visual Memorability for Robotic Interestingness via Unsupervised Online Learning

Chen Wang, Wenshan Wang, Yuheng Qiu +2

In this paper, we explore the problem of interesting scene prediction for mobile robots. This area is currently underexplored but is crucial for many practical applications such as…