activity
20152022
most citedDomain-invariant NBV Planner for Active Cross-domain Self-localization

3 citations · 6 across the 14 of their papers we have counts for

collaborators

17 papers

cs.CV2022

Domain Invariant Siamese Attention Mask for Small Object Change Detection via Everyday Indoor Robot Navigation

Koji Takeda, Kanji Tanaka, Yoshimasa Nakamura

The problem of image change detection via everyday indoor robot navigation is explored from a novel perspective of the self-attention technique. Detecting semantically non-distinct…

cs.CV2022

Exploring Self-Attention for Visual Intersection Classification

Haruki Nakata, Kanji Tanaka, Koji Takeda

In robot vision, self-attention has recently emerged as a technique for capturing non-local contexts. In this study, we introduced a self-attention mechanism into the intersection…

cs.RO2022

Minimum Cost Multicuts for Incorrect Landmark Edge Detection in Pose-graph SLAM

Kazushi Aiba, Kanji Tanaka, Ryogo Yamamoto

Pose-graph SLAM is the de facto standard framework for constructing large-scale maps from multi-session experiences of relative observations and motions during visual robot navigat…

cs.CV2021

TaylorMade VDD: Domain-adaptive Visual Defect Detector for High-mix Low-volume Production of Non-convex Cylindrical Metal Objects

Kyosuke Tashiro, Koji Takeda, Kanji Tanaka +1

Visual defect detection (VDD) for high-mix low-volume production of non-convex metal objects, such as high-pressure cylindrical piping joint parts (VDD-HPPPs), is challenging becau…

cs.CV20213 cited

Domain-invariant NBV Planner for Active Cross-domain Self-localization

Kanji Tanaka

Pole-like landmark has received increasing attention as a domain-invariant visual cue for visual robot self-localization across domains (e.g., seasons, times of day, weathers). How…

cs.CV2020

Dark Reciprocal-Rank: Boosting Graph-Convolutional Self-Localization Network via Teacher-to-student Knowledge Transfer

Koji Takeda, Kanji Tanaka

In visual robot self-localization, graph-based scene representation and matching have recently attracted research interest as robust and discriminative methods for selflocalization…