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most citedBalanced Multimodal Learning via On-the-fly Gradient Modulation

13 citations · 20 across the 7 of their papers we have counts for

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6 papers · 1 filter

cs.CV2023★ 2 cited

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…

cs.CV2023

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…

cs.CV2022★ 2 cited

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…

cs.CV2022★ 13 cited

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,…

cs.CV2022★ 2 cited

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…

cs.CV2021★ 1 cited

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…