2 citations · 4 across the 10 of their papers we have counts for
10 papers
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…
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…
Multi Positive Contrastive Learning with Pose-Consistent Generated Images
Sho Inayoshi, Aji Resindra Widya, Satoshi Ozaki +2
Model pre-training has become essential in various recognition tasks. Meanwhile, with the remarkable advancements in image generation models, pre-training methods utilizing generat…
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…