activity
20192021
most citedA Hybrid Compact Neural Architecture for Visual Place Recognition

58 citations · 83 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV20213 cited

Sequential Place Learning: Heuristic-Free High-Performance Long-Term Place Recognition

Marvin Chancán, Michael Milford

Sequential matching using hand-crafted heuristics has been standard practice in route-based place recognition for enhancing pairwise similarity results for nearly a decade. However…

cs.CV202013 cited

DeepSeqSLAM: A Trainable CNN+RNN for Joint Global Description and Sequence-based Place Recognition

Marvin Chancán, Michael Milford

Sequence-based place recognition methods for all-weather navigation are well-known for producing state-of-the-art results under challenging day-night or summer-winter transitions.…

cs.RO20201 cited

Robot Perception enables Complex Navigation Behavior via Self-Supervised Learning

Marvin Chancán, Michael Milford

Learning visuomotor control policies in robotic systems is a fundamental problem when aiming for long-term behavioral autonomy. Recent supervised-learning-based vision and motion p…

cs.RO20208 cited

MVP: Unified Motion and Visual Self-Supervised Learning for Large-Scale Robotic Navigation

Marvin Chancán, Michael Milford

Autonomous navigation emerges from both motion and local visual perception in real-world environments. However, most successful robotic motion estimation methods (e.g. VO, SLAM, Sf…

cs.CV201958 cited

A Hybrid Compact Neural Architecture for Visual Place Recognition

Marvin Chancán, Luis Hernandez-Nunez, Ajay Narendra +2

State-of-the-art algorithms for visual place recognition, and related visual navigation systems, can be broadly split into two categories: computer-science-oriented models includin…

cs.RO2019

CityLearn: Diverse Real-World Environments for Sample-Efficient Navigation Policy Learning

Marvin Chancán, Michael Milford

Visual navigation tasks in real-world environments often require both self-motion and place recognition feedback. While deep reinforcement learning has shown success in solving the…