1 citations · 1 across the 8 of their papers we have counts for
8 papers
BasketLiDAR: The First LiDAR-Camera Multimodal Dataset for Professional Basketball MOT
Ryunosuke Hayashi, Kohei Torimi, Rokuto Nagata +6
Real-time 3D trajectory player tracking in sports plays a crucial role in tactical analysis, performance evaluation, and enhancing spectator experience. Traditional systems rely on…
Leveraging LLMs with Iterative Loop Structure for Enhanced Social Intelligence in Video Question Answering
Erika Mori, Yue Qiu, Hirokatsu Kataoka +1
Social intelligence, the ability to interpret emotions, intentions, and behaviors, is essential for effective communication and adaptive responses. As robots and AI systems become…
BoundMatch: Boundary detection applied to semi-supervised segmentation
Haruya Ishikawa, Yoshimitsu Aoki
Semi-supervised semantic segmentation (SS-SS) aims to mitigate the heavy annotation burden of dense pixel labeling by leveraging abundant unlabeled images alongside a small labeled…
Text-guided Synthetic Geometric Augmentation for Zero-shot 3D Understanding
Kohei Torimi, Ryosuke Yamada, Daichi Otsuka +4
Zero-shot recognition models require extensive training data for generalization. However, in zero-shot 3D classification, collecting 3D data and captions is costly and laborintensi…
Rethinking Image Super-Resolution from Training Data Perspectives
Go Ohtani, Ryu Tadokoro, Ryosuke Yamada +7
In this work, we investigate the understudied effect of the training data used for image super-resolution (SR). Most commonly, novel SR methods are developed and benchmarked on com…
TAG: Guidance-free Open-Vocabulary Semantic Segmentation
Yasufumi Kawano, Yoshimitsu Aoki
Semantic segmentation is a crucial task in computer vision, where each pixel in an image is classified into a category. However, traditional methods face significant challenges, in…
MaskDiffusion: Exploiting Pre-trained Diffusion Models for Semantic Segmentation
Yasufumi Kawano, Yoshimitsu Aoki
Semantic segmentation is essential in computer vision for various applications, yet traditional approaches face significant challenges, including the high cost of annotation and ex…
PCT: Perspective Cue Training Framework for Multi-Camera BEV Segmentation
Haruya Ishikawa, Takumi Iida, Yoshinori Konishi +1
Generating annotations for bird's-eye-view (BEV) segmentation presents significant challenges due to the scenes' complexity and the high manual annotation cost. In this work, we ad…