2 citations · 3 across the 7 of their papers we have counts for
5 papers · 1 filter
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…
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…
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…