Deep Learning for Semantic Visual Navigation


June 16 2019

Long Beach Convention Center

Hall 103B

in conjunction with CVPR 2019

Visual navigation, the ability of an autonomous agent to find its way in a large, visually complex environment based on visual information, is a fundamental problem in computer vision and robotics.

This workshop provides a forum to promising ideas proposing to advance visual navigation by combining recent developments in deep and reinforcement learning. A special focus lies on approaches that incorporate more semantic information into navigation, and combine visual input with other modalities such as language.

Topics

Deep Reinforcement Learning for Navigation

Deep Learning for Planning and Reasoning

Representations for Navigation

Vision-Based, Semantic SLAM

Learning methods for SLAM

3D Image Understanding

Simulation Environments for Navigation and Control

Language and Robot Navigation

Object Detection, Segmentation for Robot Navigation

June 16, 2019

Long Beach Convention Center

Hall 103B


Schedule

08:40- 08:45 Welcoming

8:45 - 09:20 Invited Talk:

Georgia Gkioxari, FAIR,

Embodied Vision

09:20 - 10:00 Invited Talk:

Jana Kosecka, GMU

Generalizable Visual Representations for Navigation and Visuomotor Control

10:00 - 10:45 Poster session + Refreshments

10:45 - 11:20

Ruslan Salakhutdinov, CMU

Action Navigation Networks -- Winner of Habitat Challenge

11:20 - 12:00 Invited Talk:

Amir Zamir, Stanford University,

Learning to Navigate using Mid-level Visual Priors: Enhanced Generalization and Sample Efficiency

12:00 - 13:30 Lunch

13:30 - 14:05 Brandon Rothrock

14:05 - 14:45

Vladlen Koltun, Intel

Does Computer Vision Matter for Science?

14:45 - 15:15 Poster Session

15:15 - 15:55 Invited Talk:

Jitendra Malik, UC Berkeley and FAIR,

Visually Guided Navigation - the Role of Mapping, Landmarks and Learning

15:55 - 16:30 Panel Discussion

Participants: Jana Kosecka, Russ Salakhudinov, Andy Davison, Brandon Rothrock, Amir Zamir

Papers

Learning to Follow Directions in Street View, Karl Moritz Hermann, Mateusz Malinowski, Piotr Mirowski, Andras Banki-Horvath, Keith Anderson, Raia Hadsell

Robustness Meets Deep Learning: An End-to-End Hybrid Pipeline for Unsupervised Learning of Egomotion, Alex Zihao Zhu, Wenxin Liu, Ziyun Wang, Vijay Kumar, Kostas Daniilidis

Gibson Env V2: Embodied Simulation Environments for Interactive Navigation, Fei Xia, Chengshu Li, Kevin Chen, Roberto Martin-Martin, Noriaki Hirose, Amir R. Zamir, Silvio Savarese

Combining Optimal Control and Learning for Visual Navigation in Novel Environments, Somil Bansal, Varun Tolani, Saurabh Gupta, Jitendra Malik, Claire Tomlin

Visual Landmark Selection for Generating Grounded and Interpretable Navigation Instructions, Sanyam Agarwal, Devi Parikh, Dhruv Batra, Peter Anderson, Stefan Lee

Two Body Problem: Collaborative Visual Task Completion, Unnat Jain, Luca Weihs, Eric Kolve, Mohammad Rastegari, Svetlana Lazebnik, Ali Farhadi, Alexander Schwing, Aniruddha Kembhavi

Scene Motion Decomposition for Learnable Visual Odometry, Igor Slinko, Anna Vorontsova, Filipp Konokhov, Olga Barinova, Anton Konushin

Are You Looking? Grounding to Multiple Modalities in Vision-and-Language Navigation, Ronghang Hu, Daniel Fried, Anna Rohrbach, Dan Klein, Trevor Darrell, Kate Saenko

Viewpoint Optimization for Autonomous Strawberry Harvesting with Deep Reinforcement learning, Jonathon Sather, Xiaozheng Jane Zhang

Learning Navigation Subroutines by Watching Videos, Ashish Kumar, Saurabh Gupta, Jitendra Malik

Speakers

Jitendra Malik

UC Berkeley & FAIR

Vladlen Koltun

Intel Labs

Jana Kosecka

George Mason University

Ruslan Salakhutdinov

CMU

Georgia Gkioxari

FAIR

Brandon Rothrock

JPL

Amir Zamir

Stanford University

Submission Details

The workshop accepts 2 page abstracts up to 8 page full papers. The paper should be formatted the same way a conference submission to CVPR is formatted.

Each paper will be reviewed by at least two reviewers. The workshop accepts double submissions. The reviewing process is single blind, i.e. the reviewer will know the authors but the other way around.

The accepted papers will be linked online on the workshop website. They will not be part of the CVPR proceedings or otherwise archived.

The submission webpage is under: https://cmt3.research.microsoft.com/SEMNAV2019, and the deadline is March 25th.

Organizers

Alexander Toshev

toshev@google.com

Google AI

Anelia Angelova

anelia@google.com

Google AI

Niko Sünderhauf

niko.suenderhauf@qut.edu.au

Australian Center for Robotic Vision & Queensland University of Technology

Ronald Clark

ronald.clark@imperial.ac.uk

Imperial College London

Andrew Davison

ajd@doc.ic.ac.uk

Imperial College London

Program Committee

Alexey Dosovitskiy, Intel Labs,

Angel Xuan Chang, Eloquent Labs

Arsalan Mousavian, NVIDIA

Daniel Gordon, University of Washington

Gim Hee Lee, National University Singapore

Honglak Lee, University of Michigan and Google Research

Manolis Savva, Simon Fraser University

Piotr Mirowski, DeepMind

Saurabh Gupta, FAIR / UIUC

Zeeshan Zia, Microsoft