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20202023
most citedLook, Listen, and Attend: Co-Attention Network for Self-Supervised Audio-Visual Representation Learning

93 citations · 124 across the 14 of their papers we have counts for

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Showing 2022Show all

9 papers · 1 filter

eess.IV2022

Boosting COVID-19 Severity Detection with Infection-aware Contrastive Mixup Classification

Junlin Hou, Jilan Xu, Nan Zhang +3

This paper presents our solution for the 2nd COVID-19 Severity Detection Competition. This task aims to distinguish the Mild, Moderate, Severe, and Critical grades in COVID-19 ches…

cs.CV2022★ 2 cited

Cross-Field Transformer for Diabetic Retinopathy Grading on Two-field Fundus Images

Junlin Hou, Jilan Xu, Fan Xiao +6

Automatic diabetic retinopathy (DR) grading based on fundus photography has been widely explored to benefit the routine screening and early treatment. Existing researches generally…

eess.IV2022

CMC v2: Towards More Accurate COVID-19 Detection with Discriminative Video Priors

Junlin Hou, Jilan Xu, Nan Zhang +4

This paper presents our solution for the 2nd COVID-19 Competition, occurring in the framework of the AIMIA Workshop at the European Conference on Computer Vision (ECCV 2022). In ou…

eess.IV2022★ 2 cited

Deep-OCTA: Ensemble Deep Learning Approaches for Diabetic Retinopathy Analysis on OCTA Images

Junlin Hou, Fan Xiao, Jilan Xu +3

The ultra-wide optical coherence tomography angiography (OCTA) has become an important imaging modality in diabetic retinopathy (DR) diagnosis. However, there are few researches fo…

cs.CV2022★ 7 cited

IDEA: Increasing Text Diversity via Online Multi-Label Recognition for Vision-Language Pre-training

Xinyu Huang, Youcai Zhang, Ying Cheng +7

Vision-Language Pre-training (VLP) with large-scale image-text pairs has demonstrated superior performance in various fields. However, the image-text pairs co-occurrent on the Inte…

cs.CV2022★ 1 cited

Modality-Aware Contrastive Instance Learning with Self-Distillation for Weakly-Supervised Audio-Visual Violence Detection

Jiashuo Yu, Jinyu Liu, Ying Cheng +2

Weakly-supervised audio-visual violence detection aims to distinguish snippets containing multimodal violence events with video-level labels. Many prior works perform audio-visual…