17 citations · 37 across the 13 of their papers we have counts for
9 papers · 1 filter
PADDLES: Phase-Amplitude Spectrum Disentangled Early Stopping for Learning with Noisy Labels
Huaxi Huang, Hui Kang, Sheng Liu +4
Convolutional Neural Networks (CNNs) have demonstrated superiority in learning patterns, but are sensitive to label noises and may overfit noisy labels during training. The early s…
Cross-Modal Contrastive Learning for Robust Reasoning in VQA
Qi Zheng, Chaoyue Wang, Daqing Liu +2
Multi-modal reasoning in visual question answering (VQA) has witnessed rapid progress recently. However, most reasoning models heavily rely on shortcuts learned from training data,…
CNN-based Local Vision Transformer for COVID-19 Diagnosis
Hongyan Xu, Xiu Su, Dadong Wang
Deep learning technology can be used as an assistive technology to help doctors quickly and accurately identify COVID-19 infections. Recently, Vision Transformer (ViT) has shown gr…
Multi-scale alignment and Spatial ROI Module for COVID-19 Diagnosis
Hongyan Xu, Dadong Wang, Arcot Sowmya
Coronavirus Disease 2019 (COVID-19) has spread globally and become a health crisis faced by humanity since first reported. Radiology imaging technologies such as computer tomograph…
Bypass Network for Semantics Driven Image Paragraph Captioning
Qi Zheng, Chaoyue Wang, Dadong Wang
Image paragraph captioning aims to describe a given image with a sequence of coherent sentences. Most existing methods model the coherence through the topic transition that dynamic…
MSR: Making Self-supervised learning Robust to Aggressive Augmentations
Yingbin Bai, Erkun Yang, Zhaoqing Wang +5
Most recent self-supervised learning methods learn visual representation by contrasting different augmented views of images. Compared with supervised learning, more aggressive augm…