1 citations · 2 across the 7 of their papers we have counts for
8 papers
ProMoDD: Dataset Distillation for 3D Human Motion via Prototype-Conditioned Diffusion Models
Yijin Wei, Yawen Zou, Wenqi Cai +5
Dataset distillation (DD) aims to retain the training utility of a large dataset in a much smaller set of examples. For skeleton-based action recognition, this requires capturing d…
VT-3DAD: Cross-Category 3D Anomaly Detection via Visual-Text Normal Space Alignment
Zi Wang, Katsuya Hotta, Yawen Zou +4
Few-shot cross-category 3D anomaly detection aims to determine whether an unknown point cloud belongs to a target normal category using only a few normal references. Existing train…
DMP-3DAD: Cross-Category 3D Anomaly Detection via Realistic Depth Map Projection with Few Normal Samples
Zi Wang, Katsuya Hotta, Koichiro Kamide +4
Cross-category anomaly detection for 3D point clouds aims to determine whether an unseen object belongs to a target category using only a few normal examples. Most existing methods…
3D Human-Human Interaction Anomaly Detection
Shun Maeda, Chunzhi Gu, Koichiro Kamide +3
Human-centric anomaly detection (AD) has been primarily studied to specify anomalous behaviors in a single person. However, as humans by nature tend to act in a collaborative manne…
3DKeyAD: High-Resolution 3D Point Cloud Anomaly Detection via Keypoint-Guided Point Clustering
Zi Wang, Katsuya Hotta, Koichiro Kamide +3
High-resolution 3D point clouds are highly effective for detecting subtle structural anomalies in industrial inspection. However, their dense and irregular nature imposes significa…
Diverse Code Query Learning for Speech-Driven Facial Animation
Chunzhi Gu, Shigeru Kuriyama, Katsuya Hotta
Speech-driven facial animation aims to synthesize lip-synchronized 3D talking faces following the given speech signal. Prior methods to this task mostly focus on pursuing realism w…
Subspace-Guided Feature Reconstruction for Unsupervised Anomaly Localization
Katsuya Hotta, Chao Zhang, Yoshihiro Hagihara +1
Unsupervised anomaly localization aims to identify anomalous regions that deviate from normal sample patterns. Most recent methods perform feature matching or reconstruction for th…
PMSSC: Parallelizable multi-subset based self-expressive model for subspace clustering
Katsuya Hotta, Takuya Akashi, Shogo Tokai +1
Subspace clustering methods which embrace a self-expressive model that represents each data point as a linear combination of other data points in the dataset provide powerful unsup…