13 citations · 20 across the 7 of their papers we have counts for
7 papers
Trapped by simplicity: When Transformers fail to learn from noisy features
Evan Peters, Ando Deng, Matheus H. Zambianco +2
Noise is ubiquitous in data used to train large language models, but it is not well understood whether these models are able to correctly generalize to inputs generated without noi…
Robust Cross-Modal Knowledge Distillation for Unconstrained Videos
Wenke Xia, Xingjian Li, Andong Deng +3
Cross-modal distillation has been widely used to transfer knowledge across different modalities, enriching the representation of the target unimodal one. Recent studies highly rela…
A Large-scale Study of Spatiotemporal Representation Learning with a New Benchmark on Action Recognition
Andong Deng, Taojiannan Yang, Chen Chen
The goal of building a benchmark (suite of datasets) is to provide a unified protocol for fair evaluation and thus facilitate the evolution of a specific area. Nonetheless, we poin…
Language-Assisted Deep Learning for Autistic Behaviors Recognition
Andong Deng, Taojiannan Yang, Chen Chen +3
Correctly recognizing the behaviors of children with Autism Spectrum Disorder (ASD) is of vital importance for the diagnosis of Autism and timely early intervention. However, the o…
Balanced Multimodal Learning via On-the-fly Gradient Modulation
Xiaokang Peng, Yake Wei, Andong Deng +2
Multimodal learning helps to comprehensively understand the world, by integrating different senses. Accordingly, multiple input modalities are expected to boost model performance,…
Towards Inadequately Pre-trained Models in Transfer Learning
Andong Deng, Xingjian Li, Di Hu +3
Pre-training has been a popular learning paradigm in deep learning era, especially in annotation-insufficient scenario. Better ImageNet pre-trained models have been demonstrated, f…
Regularity Learning via Explicit Distribution Modeling for Skeletal Video Anomaly Detection
Shoubin Yu, Zhongyin Zhao, Haoshu Fang +6
Anomaly detection in surveillance videos is challenging and important for ensuring public security. Different from pixel-based anomaly detection methods, pose-based methods utilize…