14 citations · 31 across the 5 of their papers we have counts for
5 papers · 1 filter
Multi-modal Alignment using Representation Codebook
Jiali Duan, Liqun Chen, Son Tran +4
Aligning signals from different modalities is an important step in vision-language representation learning as it affects the performance of later stages such as cross-modality fusi…
Vision-Language Pre-Training with Triple Contrastive Learning
Jinyu Yang, Jiali Duan, Son Tran +6
Vision-language representation learning largely benefits from image-text alignment through contrastive losses (e.g., InfoNCE loss). The success of this alignment strategy is attrib…
Exploring Robustness of Unsupervised Domain Adaptation in Semantic Segmentation
Jinyu Yang, Chunyuan Li, Weizhi An +5
Recent studies imply that deep neural networks are vulnerable to adversarial examples -- inputs with a slight but intentional perturbation are incorrectly classified by the network…
Context-Aware Domain Adaptation in Semantic Segmentation
Jinyu Yang, Weizhi An, Chaochao Yan +2
In this paper, we consider the problem of unsupervised domain adaptation in the semantic segmentation. There are two primary issues in this field, i.e., what and how to transfer do…
Label-Driven Reconstruction for Domain Adaptation in Semantic Segmentation
Jinyu Yang, Weizhi An, Sheng Wang +3
Unsupervised domain adaptation enables to alleviate the need for pixel-wise annotation in the semantic segmentation. One of the most common strategies is to translate images from t…