8 citations · 9 across the 3 of their papers we have counts for
6 papers
Data-Driven Off-Policy Estimator Selection: An Application in User Marketing on An Online Content Delivery Service
Yuta Saito, Takuma Udagawa, Kei Tateno
Off-policy evaluation (OPE) is the method that attempts to estimate the performance of decision making policies using historical data generated by different policies without conduc…
SceneGraphFusion: Incremental 3D Scene Graph Prediction from RGB-D Sequences
Shun-Cheng Wu, Johanna Wald, Keisuke Tateno +2
Scene graphs are a compact and explicit representation successfully used in a variety of 2D scene understanding tasks. This work proposes a method to incrementally build up semanti…
A Divide et Impera Approach for 3D Shape Reconstruction from Multiple Views
Riccardo Spezialetti, David Joseph Tan, Alessio Tonioni +2
Estimating the 3D shape of an object from a single or multiple images has gained popularity thanks to the recent breakthroughs powered by deep learning. Most approaches regress the…
SCFusion: Real-time Incremental Scene Reconstruction with Semantic Completion
Shun-Cheng Wu, Keisuke Tateno, Nassir Navab +1
Real-time scene reconstruction from depth data inevitably suffers from occlusion, thus leading to incomplete 3D models. Partial reconstructions, in turn, limit the performance of a…
Peeking Behind Objects: Layered Depth Prediction from a Single Image
Helisa Dhamo, Keisuke Tateno, Iro Laina +2
While conventional depth estimation can infer the geometry of a scene from a single RGB image, it fails to estimate scene regions that are occluded by foreground objects. This limi…
Fast and Accurate Semantic Mapping through Geometric-based Incremental Segmentation
Yoshikatsu Nakajima, Keisuke Tateno, Federico Tombari +1
We propose an efficient and scalable method for incrementally building a dense, semantically annotated 3D map in real-time. The proposed method assigns class probabilities to each…