activity
20192022
most citedDisentangled Deep Autoencoding Regularization for Robust Image Classification

2 citations · 2 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2022

HCSC: Hierarchical Contrastive Selective Coding

Yuanfan Guo, Minghao Xu, Jiawen Li +4

Hierarchical semantic structures naturally exist in an image dataset, in which several semantically relevant image clusters can be further integrated into a larger cluster with coa…

cs.CV2021

MLIM: Vision-and-Language Model Pre-training with Masked Language and Image Modeling

Tarik Arici, Mehmet Saygin Seyfioglu, Tal Neiman +5

Vision-and-Language Pre-training (VLP) improves model performance for downstream tasks that require image and text inputs. Current VLP approaches differ on (i) model architecture (…

cs.CV2021

Dynamic Dual Sampling Module for Fine-Grained Semantic Segmentation

Chen Shi, Xiangtai Li, Yanran Wu +2

Representation of semantic context and local details is the essential issue for building modern semantic segmentation models. However, the interrelationship between semantic contex…

cs.LG2019

Evaluating and Boosting Uncertainty Quantification in Classification

Xiaoyang Huang, Jiancheng Yang, Linguo Li +3

Emergence of artificial intelligence techniques in biomedical applications urges the researchers to pay more attention on the uncertainty quantification (UQ) in machine-assisted me…

cs.CV20192 cited

Disentangled Deep Autoencoding Regularization for Robust Image Classification

Zhenyu Duan, Martin Renqiang Min, Li Erran Li +3

In spite of achieving revolutionary successes in machine learning, deep convolutional neural networks have been recently found to be vulnerable to adversarial attacks and difficult…