24 citations · 40 across the 5 of their papers we have counts for
11 papers · 1 filter
Controllable Relation Disentanglement for Few-Shot Class-Incremental Learning
Yuan Zhou, Richang Hong, Yanrong Guo +3
In this paper, we propose to tackle Few-Shot Class-Incremental Learning (FSCIL) from a new perspective, i.e., relation disentanglement, which means enhancing FSCIL via disentanglin…
Embedded Heterogeneous Attention Transformer for Cross-lingual Image Captioning
Zijie Song, Zhenzhen Hu, Yuanen Zhou +3
Cross-lingual image captioning is a challenging task that requires addressing both cross-lingual and cross-modal obstacles in multimedia analysis. The crucial issue in this task is…
Advancing Incremental Few-shot Semantic Segmentation via Semantic-guided Relation Alignment and Adaptation
Yuan Zhou, Xin Chen, Yanrong Guo +3
Incremental few-shot semantic segmentation (IFSS) aims to incrementally extend a semantic segmentation model to novel classes according to only a few pixel-level annotated data, wh…
Image Captioning via Compact Bidirectional Architecture
Zijie Song, Yuanen Zhou, Zhenzhen Hu +4
Most current image captioning models typically generate captions from left-to-right. This unidirectional property makes them can only leverage past context but not future context.…
Few-shot Learning with Global Relatedness Decoupled-Distillation
Yuan Zhou, Yanrong Guo, Shijie Hao +3
Despite the success that metric learning based approaches have achieved in few-shot learning, recent works reveal the ineffectiveness of their episodic training mode. In this paper…
Semi-Autoregressive Transformer for Image Captioning
Yuanen Zhou, Yong Zhang, Zhenzhen Hu +1
Current state-of-the-art image captioning models adopt autoregressive decoders, \ie they generate each word by conditioning on previously generated words, which leads to heavy late…