35 citations · 58 across the 6 of their papers we have counts for
6 papers
Improving Label Assignments Learning by Dynamic Sample Dropout Combined with Layer-wise Optimization in Speech Separation
Chenyang Gao, Yue Gu, Ivan Marsic
In supervised speech separation, permutation invariant training (PIT) is widely used to handle label ambiguity by selecting the best permutation to update the model. Despite its su…
Chop Chop BERT: Visual Question Answering by Chopping VisualBERT's Heads
Chenyu Gao, Qi Zhu, Peng Wang +1
Vision-and-Language (VL) pre-training has shown great potential on many related downstream tasks, such as Visual Question Answering (VQA), one of the most popular problems in the V…
Simple is not Easy: A Simple Strong Baseline for TextVQA and TextCaps
Qi Zhu, Chenyu Gao, Peng Wang +1
Texts appearing in daily scenes that can be recognized by OCR (Optical Character Recognition) tools contain significant information, such as street name, product brand and prices.…
Structured Multimodal Attentions for TextVQA
Chenyu Gao, Qi Zhu, Peng Wang +4
In this paper, we propose an end-to-end structured multimodal attention (SMA) neural network to mainly solve the first two issues above. SMA first uses a structural graph represent…
Simple Lifelong Learning Machines
Jayanta Dey, Joshua T. Vogelstein, Hayden S. Helm +13
In lifelong learning, data are used to improve performance not only on the present task, but also on past and future (unencountered) tasks. While typical transfer learning algorith…
C^3 Framework: An Open-source PyTorch Code for Crowd Counting
Junyu Gao, Wei Lin, Bin Zhao +3
This technical report attempts to provide efficient and solid kits addressed on the field of crowd counting, which is denoted as Crowd Counting Code Framework (CF). The contrib…