activity
20182025
most citedSegment Anything in Medical Images

2.8k citations · 3k across the 32 of their papers we have counts for

collaborators
Showing 2021Show all

7 papers · 1 filter

cs.CV2021

MEGAN: Memory Enhanced Graph Attention Network for Space-Time Video Super-Resolution

Chenyu You, Lianyi Han, Aosong Feng +3

Space-time video super-resolution (STVSR) aims to construct a high space-time resolution video sequence from the corresponding low-frame-rate, low-resolution video sequence. Inspir…

cs.LG2021

Auto-Encoding Knowledge Graph for Unsupervised Medical Report Generation

Fenglin Liu, Chenyu You, Xian Wu +3

Medical report generation, which aims to automatically generate a long and coherent report of a given medical image, has been receiving growing research interests. Existing approac…

cs.CL2021

Self-supervised Contrastive Cross-Modality Representation Learning for Spoken Question Answering

Chenyu You, Nuo Chen, Yuexian Zou

Spoken question answering (SQA) requires fine-grained understanding of both spoken documents and questions for the optimal answer prediction. In this paper, we propose novel traini…

cs.CV2021

SimCVD: Simple Contrastive Voxel-Wise Representation Distillation for Semi-Supervised Medical Image Segmentation

Chenyu You, Yuan Zhou, Ruihan Zhao +2

Automated segmentation in medical image analysis is a challenging task that requires a large amount of manually labeled data. However, most existing learning-based approaches usual…

cs.CL2021

Self-supervised Dialogue Learning for Spoken Conversational Question Answering

Nuo Chen, Chenyu You, Yuexian Zou

In spoken conversational question answering (SCQA), the answer to the corresponding question is generated by retrieving and then analyzing a fixed spoken document, including multi-…

cs.LG2021★ 19 cited

Undistillable: Making A Nasty Teacher That CANNOT teach students

Haoyu Ma, Tianlong Chen, Ting-Kuei Hu +3

Knowledge Distillation (KD) is a widely used technique to transfer knowledge from pre-trained teacher models to (usually more lightweight) student models. However, in certain situa…