78 citations · 432 across the 28 of their papers we have counts for
11 papers · 1 filter
Rethinking Semi-Supervised Medical Image Segmentation: A Variance-Reduction Perspective
Chenyu You, Weicheng Dai, Yifei Min +5
For medical image segmentation, contrastive learning is the dominant practice to improve the quality of visual representations by contrasting semantically similar and dissimilar pa…
Aligning Source Visual and Target Language Domains for Unpaired Video Captioning
Fenglin Liu, Xian Wu, Chenyu You +3
Training supervised video captioning model requires coupled video-caption pairs. However, for many targeted languages, sufficient paired data are not available. To this end, we int…
Expectation-Maximization Contrastive Learning for Compact Video-and-Language Representations
Peng Jin, Jinfa Huang, Fenglin Liu +5
Most video-and-language representation learning approaches employ contrastive learning, e.g., CLIP, to project the video and text features into a common latent space according to t…
DiMBERT: Learning Vision-Language Grounded Representations with Disentangled Multimodal-Attention
Fenglin Liu, Xian Wu, Shen Ge +4
Vision-and-language (V-L) tasks require the system to understand both vision content and natural language, thus learning fine-grained joint representations of vision and language (…
Prophet Attention: Predicting Attention with Future Attention for Image Captioning
Fenglin Liu, Xuancheng Ren, Xian Wu +3
Recently, attention based models have been used extensively in many sequence-to-sequence learning systems. Especially for image captioning, the attention based models are expected…
Class-Aware Adversarial Transformers for Medical Image Segmentation
Chenyu You, Ruihan Zhao, Fenglin Liu +5
Transformers have made remarkable progress towards modeling long-range dependencies within the medical image analysis domain. However, current transformer-based models suffer from…
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…
Exploring and Distilling Cross-Modal Information for Image Captioning
Fenglin Liu, Xuancheng Ren, Yuanxin Liu +2
Recently, attention-based encoder-decoder models have been used extensively in image captioning. Yet there is still great difficulty for the current methods to achieve deep image u…
Non-Autoregressive Coarse-to-Fine Video Captioning
Bang Yang, Yuexian Zou, Fenglin Liu +1
It is encouraged to see that progress has been made to bridge videos and natural language. However, mainstream video captioning methods suffer from slow inference speed due to the…