activity
20182022
most citedMedical-VLBERT: Medical Visual Language BERT for COVID-19 CT Report Generation With Alternate Learning

80 citations · 180 across the 21 of their papers we have counts for

collaborators

29 papers

cs.CV202216 cited

CoupAlign: Coupling Word-Pixel with Sentence-Mask Alignments for Referring Image Segmentation

Zicheng Zhang, Yi Zhu, Jianzhuang Liu +2

Referring image segmentation aims at localizing all pixels of the visual objects described by a natural language sentence. Previous works learn to straightforwardly align the sente…

cs.CV20221 cited

Learning Self-Regularized Adversarial Views for Self-Supervised Vision Transformers

Tao Tang, Changlin Li, Guangrun Wang +3

Automatic data augmentation (AutoAugment) strategies are indispensable in supervised data-efficient training protocols of vision transformers, and have led to state-of-the-art resu…

cs.CL20221 cited

"My nose is running.""Are you also coughing?": Building A Medical Diagnosis Agent with Interpretable Inquiry Logics

Wenge Liu, Yi Cheng, Hao Wang +6

With the rise of telemedicine, the task of developing Dialogue Systems for Medical Diagnosis (DSMD) has received much attention in recent years. Different from early researches tha…

cs.CV20224 cited

Automated Progressive Learning for Efficient Training of Vision Transformers

Changlin Li, Bohan Zhuang, Guangrun Wang +3

Recent advances in vision Transformers (ViTs) have come with a voracious appetite for computing power, high-lighting the urgent need to develop efficient training methods for ViTs.…

cs.CV202111 cited

Image Comes Dancing with Collaborative Parsing-Flow Video Synthesis

Bowen Wu, Zhenyu Xie, Xiaodan Liang +3

Transferring human motion from a source to a target person poses great potential in computer vision and graphics applications. A crucial step is to manipulate sequential future mot…

cs.CV20213 cited

DS-Net++: Dynamic Weight Slicing for Efficient Inference in CNNs and Transformers

Changlin Li, Guangrun Wang, Bing Wang +3

Dynamic networks have shown their promising capability in reducing theoretical computation complexity by adapting their architectures to the input during inference. However, their…