Search Results for author: Masakazu Yoshimura

Found 9 papers, 0 papers with code

Mixed-precision Supernet Training from Vision Foundation Models using Low Rank Adapter

no code implementations29 Mar 2024 Yuiko Sakuma, Masakazu Yoshimura, Junji Otsuka, Atsushi Irie, Takeshi Ohashi

To tackle these challenges, first, we study the effective search space design for fine-tuning a VFM by comparing different operators (such as resolution, feature size, width, depth, and bit-widths) in terms of performance and BitOPs reduction.

Neural Architecture Search

PQDynamicISP: Dynamically Controlled Image Signal Processor for Any Image Sensors Pursuing Perceptual Quality

no code implementations15 Mar 2024 Masakazu Yoshimura, Junji Otsuka, Takeshi Ohashi

Full DNN-based image signal processors (ISPs) have been actively studied and have achieved superior image quality compared to conventional ISPs.

Ranked #2 on Image Enhancement on MIT-Adobe 5k (PSNR on proRGB metric)

Image Enhancement Tone Mapping

Self-Supervised Reversed Image Signal Processing via Reference-Guided Dynamic Parameter Selection

no code implementations24 Mar 2023 Junji Otsuka, Masakazu Yoshimura, Takeshi Ohashi

To tackle these limitations, we propose a self-supervised reversed ISP method that does not require metadata and paired images.

object-detection Object Detection

Efficient Joint Detection and Multiple Object Tracking with Spatially Aware Transformer

no code implementations9 Nov 2022 Siddharth Sagar Nijhawan, Leo Hoshikawa, Atsushi Irie, Masakazu Yoshimura, Junji Otsuka, Takeshi Ohashi

We propose a light-weight and highly efficient Joint Detection and Tracking pipeline for the task of Multi-Object Tracking using a fully-transformer architecture.

Multi-Object Tracking Multiple Object Tracking

DynamicISP: Dynamically Controlled Image Signal Processor for Image Recognition

no code implementations ICCV 2023 Masakazu Yoshimura, Junji Otsuka, Atsushi Irie, Takeshi Ohashi

Image Signal Processors (ISPs) play important roles in image recognition tasks as well as in the perceptual quality of captured images.

object-detection Object Detection

Rawgment: Noise-Accounted RAW Augmentation Enables Recognition in a Wide Variety of Environments

no code implementations CVPR 2023 Masakazu Yoshimura, Junji Otsuka, Atsushi Irie, Takeshi Ohashi

We show that our proposed noise-accounted RAW augmentation method doubles the image recognition accuracy in challenging environments only with simple training data.

Image Augmentation

MBAPose: Mask and Bounding-Box Aware Pose Estimation of Surgical Instruments with Photorealistic Domain Randomization

no code implementations15 Mar 2021 Masakazu Yoshimura, Murilo Marques Marinho, Kanako Harada, Mamoru Mitsuishi

Our experiments demonstrated an improvement of 21 % for translation error and 26 % for orientation error on synthetic test data with respect to our previous work.

3D Pose Estimation 6D Pose Estimation using RGB +1

FOSS: Multi-Person Age Estimation with Focusing on Objects and Still Seeing Surroundings

no code implementations15 Oct 2020 Masakazu Yoshimura, Satoshi Ogata

Usually, such situations were solved by two separate models; one is a face detector model which crops facial regions and the other is an age estimation model which estimates from cropped images.

Age Estimation

Single-Shot Pose Estimation of Surgical Robot Instruments' Shafts from Monocular Endoscopic Images

no code implementations3 Mar 2020 Masakazu Yoshimura, Murilo M. Marinho, Kanako Harada, Mamoru Mitsuishi

To avoid injuring the patients, a collision-avoidance algorithm that depends on having an accurate model for the poses of the instruments' shafts is used.

Collision Avoidance Pose Estimation

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