12 citations · 23 across the 7 of their papers we have counts for
7 papers
Fast-ParC: Capturing Position Aware Global Feature for ConvNets and ViTs
Tao Yang, Haokui Zhang, Wenze Hu +2
Transformer models have made tremendous progress in various fields in recent years. In the field of computer vision, vision transformers (ViTs) also become strong alternatives to c…
Prompt-based Learning for Unpaired Image Captioning
Peipei Zhu, Xiao Wang, Lin Zhu +4
Unpaired Image Captioning (UIC) has been developed to learn image descriptions from unaligned vision-language sample pairs. Existing works usually tackle this task using adversaria…
Unpaired Image Captioning by Image-level Weakly-Supervised Visual Concept Recognition
Peipei Zhu, Xiao Wang, Yong Luo +4
The goal of unpaired image captioning (UIC) is to describe images without using image-caption pairs in the training phase. Although challenging, we except the task can be accomplis…
Improving Contrastive Learning by Visualizing Feature Transformation
Rui Zhu, Bingchen Zhao, Jingen Liu +2
Contrastive learning, which aims at minimizing the distance between positive pairs while maximizing that of negative ones, has been widely and successfully applied in unsupervised…
Beyond Fine-tuning: Classifying High Resolution Mammograms using Function-Preserving Transformations
Tao Wei, Angelica I Aviles-Rivero, Shuo Wang +4
The task of classifying mammograms is very challenging because the lesion is usually small in the high resolution image. The current state-of-the-art approaches for medical image c…
Modularized Morphing of Neural Networks
Tao Wei, Changhu Wang, Chang Wen Chen
In this work we study the problem of network morphism, an effective learning scheme to morph a well-trained neural network to a new one with the network function completely preserv…