Search Results for author: Wenshan Wang

Found 17 papers, 7 papers with code

How Does It Feel? Self-Supervised Costmap Learning for Off-Road Vehicle Traversability

no code implementations22 Sep 2022 Mateo Guaman Castro, Samuel Triest, Wenshan Wang, Jason M. Gregory, Felix Sanchez, John G. Rogers III, Sebastian Scherer

Our short-scale navigation results show that using our learned costmaps leads to overall smoother navigation, and provides the robot with a more fine-grained understanding of the robot-terrain interactions.

DytanVO: Joint Refinement of Visual Odometry and Motion Segmentation in Dynamic Environments

2 code implementations17 Sep 2022 Shihao Shen, Yilin Cai, Wenshan Wang, Sebastian Scherer

Learning-based visual odometry (VO) algorithms achieve remarkable performance on common static scenes, benefiting from high-capacity models and massive annotated data, but tend to fail in dynamic, populated environments.

Motion Segmentation Semantic Segmentation +1

Unsupervised Online Learning for Robotic Interestingness with Visual Memory

1 code implementation18 Nov 2021 Chen Wang, Yuheng Qiu, Wenshan Wang, Yafei Hu, Seungchan Kim, Sebastian Scherer

Instead, we propose to develop a method that automatically adapts online to the environment to report interesting scenes quickly.


AirDOS: Dynamic SLAM benefits from Articulated Objects

1 code implementation21 Sep 2021 Yuheng Qiu, Chen Wang, Wenshan Wang, Mina Henein, Sebastian Scherer

To the best of our knowledge, AirDOS is the first dynamic object-aware SLAM system demonstrating that camera pose estimation can be improved by incorporating dynamic articulated objects.

Motion Estimation Pose Estimation

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

no code implementations13 Mar 2021 Yaoyu Hu, Wenshan Wang, Huai Yu, Weikun Zhen, Sebastian Scherer

Stereo reconstruction models trained on small images do not generalize well to high-resolution data.

Stereo Matching

Risk Prediction on Traffic Accidents using a Compact Neural Model for Multimodal Information Fusion over Urban Big Data

no code implementations21 Feb 2021 Wenshan Wang, Su Yang, Weishan Zhang

Predicting risk map of traffic accidents is vital for accident prevention and early planning of emergency response.

TartanVO: A Generalizable Learning-based VO

2 code implementations31 Oct 2020 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 challenging scenes.

Visual Odometry

TartanAir: A Dataset to Push the Limits of Visual SLAM

1 code implementation31 Mar 2020 Wenshan Wang, Delong Zhu, Xiangwei Wang, Yaoyu Hu, Yuheng Qiu, Chen Wang, Yafei Hu, Ashish Kapoor, Sebastian Scherer

We present a challenging dataset, the TartanAir, for robot navigation task and more.


Autonomous Aerial Cinematography In Unstructured Environments With Learned Artistic Decision-Making

no code implementations15 Oct 2019 Rogerio Bonatti, Wenshan Wang, Cherie Ho, Aayush Ahuja, Mirko Gschwindt, Efe Camci, Erdal Kayacan, Sanjiban Choudhury, Sebastian Scherer

In this work, we address the problem in its entirety and propose a complete system for real-time aerial cinematography that for the first time combines: (1) vision-based target estimation; (2) 3D signed-distance mapping for occlusion estimation; (3) efficient trajectory optimization for long time-horizon camera motion; and (4) learning-based artistic shot selection.

Decision Making Occlusion Estimation

Towards a Robust Aerial Cinematography Platform: Localizing and Tracking Moving Targets in Unstructured Environments

no code implementations4 Apr 2019 Rogerio Bonatti, Cherie Ho, Wenshan Wang, Sanjiban Choudhury, Sebastian Scherer

In this work, we overcome such limitations and propose a complete system for aerial cinematography that combines: (1) a vision-based algorithm for target localization; (2) a real-time incremental 3D signed-distance map algorithm for occlusion and safety computation; and (3) a real-time camera motion planner that optimizes smoothness, collisions, occlusions and artistic guidelines.

Pose Estimation

Improved Generalization of Heading Direction Estimation for Aerial Filming Using Semi-supervised Regression

no code implementations26 Mar 2019 Wenshan Wang, Aayush Ahuja, Yanfu Zhang, Rogerio Bonatti, Sebastian Scherer

We show that by leveraging unlabeled sequences, the amount of labeled data required can be significantly reduced.


Integrating kinematics and environment context into deep inverse reinforcement learning for predicting off-road vehicle trajectories

1 code implementation16 Oct 2018 Yanfu Zhang, Wenshan Wang, Rogerio Bonatti, Daniel Maturana, Sebastian Scherer

The first-stage network learns feature representations of the environment using low-level LiDAR statistics and the second-stage network combines those learned features with kinematics data.

Autonomous Navigation motion prediction +1

Autonomous drone cinematographer: Using artistic principles to create smooth, safe, occlusion-free trajectories for aerial filming

no code implementations28 Aug 2018 Rogerio Bonatti, yanfu Zhang, Sanjiban Choudhury, Wenshan Wang, Sebastian Scherer

Autonomous aerial cinematography has the potential to enable automatic capture of aesthetically pleasing videos without requiring human intervention, empowering individuals with the capability of high-end film studios.

Neural Aesthetic Image Reviewer

no code implementations28 Feb 2018 Wenshan Wang, Su Yang, Weishan Zhang, Jiulong Zhang

Through multi-task learning, the proposed models can rate aesthetic images as well as produce comments in an end-to-end manner.

Multi-Task Learning

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