18 citations · 44 across the 7 of their papers we have counts for
7 papers · 1 filter
Split-PU: Hardness-aware Training Strategy for Positive-Unlabeled Learning
Chengming Xu, Chen Liu, Siqian Yang +4
Positive-Unlabeled (PU) learning aims to learn a model with rare positive samples and abundant unlabeled samples. Compared with classical binary classification, the task of PU lear…
PatchMix Augmentation to Identify Causal Features in Few-shot Learning
Chengming Xu, Chen Liu, Xinwei Sun +4
The task of Few-shot learning (FSL) aims to transfer the knowledge learned from base categories with sufficient labelled data to novel categories with scarce known information. It…
Learnable Irrelevant Modality Dropout for Multimodal Action Recognition on Modality-Specific Annotated Videos
Saghir Alfasly, Jian Lu, Chen Xu +1
With the assumption that a video dataset is multimodality annotated in which auditory and visual modalities both are labeled or class-relevant, current multimodal methods apply mod…
The Image Local Autoregressive Transformer
Chenjie Cao, Yuxin Hong, Xiang Li +4
Recently, AutoRegressive (AR) models for the whole image generation empowered by transformers have achieved comparable or even better performance to Generative Adversarial Networks…
Learning Dynamic Alignment via Meta-filter for Few-shot Learning
Chengming Xu, Chen Liu, Li Zhang +5
Few-shot learning (FSL), which aims to recognise new classes by adapting the learned knowledge with extremely limited few-shot (support) examples, remains an important open problem…
Learning Salient Boundary Feature for Anchor-free Temporal Action Localization
Chuming Lin, Chengming Xu, Donghao Luo +6
Temporal action localization is an important yet challenging task in video understanding. Typically, such a task aims at inferring both the action category and localization of the…