6 citations · 8 across the 5 of their papers we have counts for
5 papers
SCALE: Semantic- and Confidence-Aware Conditional Variational Autoencoder for Zero-shot Skeleton-based Action Recognition
Soroush Oraki, Feng Ding, Jie Liang
Zero-shot skeleton-based action recognition (ZSAR) aims to recognize action classes without any training skeletons from those classes, relying instead on auxiliary semantics from t…
LSTC-MDA: A Unified Framework for Long-Short Term Temporal Convolution and Mixed Data Augmentation in Skeleton-Based Action Recognition
Feng Ding, Haisheng Fu, Soroush Oraki +1
Skeleton-based action recognition faces two longstanding challenges: the scarcity of labeled training samples and difficulty modeling short- and long-range temporal dependencies. T…
The Amazon Nova Family of Models: Technical Report and Model Card
Amazon AGI, Aaron Langford, Aayush Shah +783
We present Amazon Nova, a new generation of state-of-the-art foundation models that deliver frontier intelligence and industry-leading price performance. Amazon Nova Pro is a highl…
LORTSAR: Low-Rank Transformer for Skeleton-based Action Recognition
Soroush Oraki, Harry Zhuang, Jie Liang
The complexity of state-of-the-art Transformer-based models for skeleton-based action recognition poses significant challenges in terms of computational efficiency and resource uti…
A Multi-task Joint Framework for Real-time Person Search
Ye Li, Kangning Yin, Jie Liang +2
Person search generally involves three important parts: person detection, feature extraction and identity comparison. However, person search integrating detection, extraction and c…