115 citations · 733 across the 55 of their papers we have counts for
89 papers
Learning Conditional Attributes for Compositional Zero-Shot Learning
Qingsheng Wang, Lingqiao Liu, Chenchen Jing +4
Compositional Zero-Shot Learning (CZSL) aims to train models to recognize novel compositional concepts based on learned concepts such as attribute-object combinations. One of the c…
FoPro: Few-Shot Guided Robust Webly-Supervised Prototypical Learning
Yulei Qin, Xingyu Chen, Chao Chen +5
Recently, webly supervised learning (WSL) has been studied to leverage numerous and accessible data from the Internet. Most existing methods focus on learning noise-robust models f…
Learning from partially labeled data for multi-organ and tumor segmentation
Yutong Xie, Jianpeng Zhang, Yong Xia +1
Medical image benchmarks for the segmentation of organs and tumors suffer from the partially labeling issue due to its intensive cost of labor and expertise. Current mainstream app…
Hierarchical Normalization for Robust Monocular Depth Estimation
Chi Zhang, Wei Yin, Zhibin Wang +3
In this paper, we address monocular depth estimation with deep neural networks. To enable training of deep monocular estimation models with various sources of datasets, state-of-th…
Text-Adaptive Multiple Visual Prototype Matching for Video-Text Retrieval
Chengzhi Lin, Ancong Wu, Junwei Liang +4
Cross-modal retrieval between videos and texts has gained increasing research interest due to the rapid emergence of videos on the web. Generally, a video contains rich instance an…
PyramidCLIP: Hierarchical Feature Alignment for Vision-language Model Pretraining
Yuting Gao, Jinfeng Liu, Zihan Xu +4
Large-scale vision-language pre-training has achieved promising results on downstream tasks. Existing methods highly rely on the assumption that the image-text pairs crawled from t…