23 citations · 34 across the 16 of their papers we have counts for
17 papers
VIF-Bench: Evaluating Visual Instruction Following in Multi-Reference Image Generation
Yuta Oshima, Masakazu Yoshimura, Masahiro Suzuki +2
Recent multimodal image generation models can take multiple images and textual instructions as input, enabling reference-based generation guided not only by text but also by visual…
Structuring Open-Ended NAS: Semi-Automated Design Knowledge Structuring with LLMs for Efficient Neural Architecture Search
Yuiko Sakuma, Masakazu Yoshimura, Marcel Gröpl +4
Current neural architecture search (NAS) methods are often limited by their predefined, restrictive search spaces. While recent large language model (LLM)-assisted NAS methods enab…
LLM as a Tool, Not an Agent: Code-Mined Tree Transformations for Neural Architecture Search
Masakazu Yoshimura, Zitang Sun, Yuiko Sakuma +3
Neural Architecture Search (NAS) aims to automatically discover high-performing deep neural network (DNN) architectures. However, conventional algorithm-driven NAS relies on carefu…
SF-Mamba: Rethinking State Space Model for Vision
Masakazu Yoshimura, Teruaki Hayashi, Yuki Hoshino +2
Visual Mamba models have recently emerged as alternatives to Vision Transformers (ViTs), which suffer from quadratic complexity. While the recurrent scanning mechanism of Mamba off…
Online Data Curation for Object Detection via Marginal Contributions to Dataset-level Average Precision
Zitang Sun, Masakazu Yoshimura, Junji Otsuka +2
High-quality data has become a primary driver of progress under scale laws, with curated datasets often outperforming much larger unfiltered ones at lower cost. Online data curatio…
SemiISP/SemiIE: Semi-Supervised Image Signal Processor and Image Enhancement Leveraging One-to-Many Mapping sRGB-to-RAW
Masakazu Yoshimura, Junji Otsuka, Radu Berdan +1
DNN-based methods have been successful in Image Signal Processor (ISP) and image enhancement (IE) tasks. However, the cost of creating training data for these tasks is considerably…
Beyond RGB: Adaptive Parallel Processing for RAW Object Detection
Shani Gamrian, Hila Barel, Feiran Li +2
Object detection models are typically applied to standard RGB images processed through Image Signal Processing (ISP) pipelines, which are designed to enhance sensor-captured RAW im…
MambaPEFT: Exploring Parameter-Efficient Fine-Tuning for Mamba
Masakazu Yoshimura, Teruaki Hayashi, Yota Maeda
An ecosystem of Transformer-based models has been established by building large models with extensive data. Parameter-efficient fine-tuning (PEFT) is a crucial technology for deplo…
Mixed-precision Supernet Training from Vision Foundation Models using Low Rank Adapter
Yuiko Sakuma, Masakazu Yoshimura, Junji Otsuka +2
Compression of large and performant vision foundation models (VFMs) into arbitrary bit-wise operations (BitOPs) allows their deployment on various hardware. We propose to fine-tune…
PQDynamicISP: Dynamically Controlled Image Signal Processor for Any Image Sensors Pursuing Perceptual Quality
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. In contrast to this trend, we propo…
Self-Supervised Reversed Image Signal Processing via Reference-Guided Dynamic Parameter Selection
Junji Otsuka, Masakazu Yoshimura, Takeshi Ohashi
Unprocessed sensor outputs (RAW images) potentially improve both low-level and high-level computer vision algorithms, but the lack of large-scale RAW image datasets is a barrier to…
Efficient Joint Detection and Multiple Object Tracking with Spatially Aware Transformer
Siddharth Sagar Nijhawan, Leo Hoshikawa, Atsushi Irie +3
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. It is a modified…
DynamicISP: Dynamically Controlled Image Signal Processor for Image Recognition
Masakazu Yoshimura, Junji Otsuka, Atsushi Irie +1
Image Signal Processors (ISPs) play important roles in image recognition tasks as well as in the perceptual quality of captured images. In most cases, experts make a lot of effort…
Rawgment: Noise-Accounted RAW Augmentation Enables Recognition in a Wide Variety of Environments
Masakazu Yoshimura, Junji Otsuka, Atsushi Irie +1
Image recognition models that work in challenging environments (e.g., extremely dark, blurry, or high dynamic range conditions) must be useful. However, creating training datasets…
MBAPose: Mask and Bounding-Box Aware Pose Estimation of Surgical Instruments with Photorealistic Domain Randomization
Masakazu Yoshimura, Murilo Marques Marinho, Kanako Harada +1
Surgical robots are usually controlled using a priori models based on the robots' geometric parameters, which are calibrated before the surgical procedure. One of the challenges in…
FOSS: Multi-Person Age Estimation with Focusing on Objects and Still Seeing Surroundings
Masakazu Yoshimura, Satoshi Ogata
Age estimation from images can be used in many practical scenes. Most of the previous works targeted on the estimation from images in which only one face exists. Also, most of the…
Single-Shot Pose Estimation of Surgical Robot Instruments' Shafts from Monocular Endoscopic Images
Masakazu Yoshimura, Murilo M. Marinho, Kanako Harada +1
Surgical robots are used to perform minimally invasive surgery and alleviate much of the burden imposed on surgeons. Our group has developed a surgical robot to aid in the removal…