3 citations · 5 across the 7 of their papers we have counts for
7 papers
Modeling Multi-modal Cross-interaction for Multi-label Few-shot Image Classification Based on Local Feature Selection
Kun Yan, Zied Bouraoui, Fangyun Wei +4
The aim of multi-label few-shot image classification (ML-FSIC) is to assign semantic labels to images, in settings where only a small number of training examples are available for…
Two-shot Video Object Segmentation
Kun Yan, Xiao Li, Fangyun Wei +4
Previous works on video object segmentation (VOS) are trained on densely annotated videos. Nevertheless, acquiring annotations in pixel level is expensive and time-consuming. In th…
An Efficient COarse-to-fiNE Alignment Framework @ Ego4D Natural Language Queries Challenge 2022
Zhijian Hou, Wanjun Zhong, Lei Ji +6
This technical report describes the CONE approach for Ego4D Natural Language Queries (NLQ) Challenge in ECCV 2022. We leverage our model CONE, an efficient window-centric COarse-to…
Inferring Prototypes for Multi-Label Few-Shot Image Classification with Word Vector Guided Attention
Kun Yan, Chenbin Zhang, Jun Hou +4
Multi-label few-shot image classification (ML-FSIC) is the task of assigning descriptive labels to previously unseen images, based on a small number of training examples. A key fea…
CETransformer: Casual Effect Estimation via Transformer Based Representation Learning
Zhenyu Guo, Shuai Zheng, Zhizhe Liu +2
Treatment effect estimation, which refers to the estimation of causal effects and aims to measure the strength of the causal relationship, is of great importance in many fields but…
Aligning Visual Prototypes with BERT Embeddings for Few-Shot Learning
Kun Yan, Zied Bouraoui, Ping Wang +2
Few-shot learning (FSL) is the task of learning to recognize previously unseen categories of images from a small number of training examples. This is a challenging task, as the ava…
Few-shot Image Classification with Multi-Facet Prototypes
Kun Yan, Zied Bouraoui, Ping Wang +2
The aim of few-shot learning (FSL) is to learn how to recognize image categories from a small number of training examples. A central challenge is that the available training exampl…