Search Results for author: Rin-ichiro Taniguchi

Found 8 papers, 1 papers with code

TetraTSDF: 3D human reconstruction from a single image with a tetrahedral outer shell

1 code implementation CVPR 2020 Hayato Onizuka, Zehra Hayirci, Diego Thomas, Akihiro Sugimoto, Hideaki Uchiyama, Rin-ichiro Taniguchi

In this paper, we propose the tetrahedral outer shell volumetric truncated signed distance function (TetraTSDF) model for the human body, and its corresponding part connection network (PCN) for 3D human body shape regression.

3D Human Reconstruction regression

Joint optimization for compressive video sensing and reconstruction under hardware constraints

no code implementations ECCV 2018 Michitaka Yoshida, Akihiko Torii, Masatoshi Okutomi, Kenta Endo, Yukinobu Sugiyama, Rin-ichiro Taniguchi, Hajime Nagahara

Compressive video sensing is the process of encoding multiple sub-frames into a single frame with controlled sensor exposures and reconstructing the sub-frames from the single compressed frame.

Compressive Sensing

Augmented Blendshapes for Real-Time Simultaneous 3D Head Modeling and Facial Motion Capture

no code implementations CVPR 2016 Diego Thomas, Rin-ichiro Taniguchi

Our framework is the first one to provide simultaneously comprehensive facial motion tracking and a detailed 3D model of the user's head.

Shape and Light Directions From Shading and Polarization

no code implementations CVPR 2015 Trung Ngo Thanh, Hajime Nagahara, Rin-ichiro Taniguchi

In contrast, photometric stereo method with multiple light sources can disambiguate the surface orientation and give a strong relationship between the surface normals and light directions.

Background Modeling Based on Bidirectional Analysis

no code implementations CVPR 2013 Atsushi Shimada, Hajime Nagahara, Rin-ichiro Taniguchi

Although a result will be output with some delay because information is taken from a future period, our proposed approach improves the accuracy by about 30% if only a 33-millisecond of delay is acceptable.

Light Field Distortion Feature for Transparent Object Recognition

no code implementations CVPR 2013 Kazuki Maeno, Hajime Nagahara, Atsushi Shimada, Rin-ichiro Taniguchi

These approaches though cannot apply to transparent objects made of glass or plastic, as such objects take on the visual features of background objects, and the appearance of such objects dramatically varies with changes in scene background.

Object Object Recognition +1

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