78 citations · 432 across the 28 of their papers we have counts for
7 papers · 1 filter
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…
O2NA: An Object-Oriented Non-Autoregressive Approach for Controllable Video Captioning
Fenglin Liu, Xuancheng Ren, Xian Wu +4
Video captioning combines video understanding and language generation. Different from image captioning that describes a static image with details of almost every object, video capt…
Audio-Oriented Multimodal Machine Comprehension: Task, Dataset and Model
Zhiqi Huang, Fenglin Liu, Xian Wu +4
While Machine Comprehension (MC) has attracted extensive research interests in recent years, existing approaches mainly belong to the category of Machine Reading Comprehension task…
Exploring and Distilling Posterior and Prior Knowledge for Radiology Report Generation
Fenglin Liu, Xian Wu, Shen Ge +2
Automatically generating radiology reports can improve current clinical practice in diagnostic radiology. On one hand, it can relieve radiologists from the heavy burden of report w…
Exploring Semantic Relationships for Unpaired Image Captioning
Fenglin Liu, Meng Gao, Tianhao Zhang +1
Recently, image captioning has aroused great interest in both academic and industrial worlds. Most existing systems are built upon large-scale datasets consisting of image-sentence…
Contrastive Attention for Automatic Chest X-ray Report Generation
Fenglin Liu, Changchang Yin, Xian Wu +4
Recently, chest X-ray report generation, which aims to automatically generate descriptions of given chest X-ray images, has received growing research interests. The key challenge o…
Rethinking Skip Connection with Layer Normalization in Transformers and ResNets
Fenglin Liu, Xuancheng Ren, Zhiyuan Zhang +2
Skip connection, is a widely-used technique to improve the performance and the convergence of deep neural networks, which is believed to relieve the difficulty in optimization due…