26 citations · 70 across the 12 of their papers we have counts for
5 papers · 1 filter
Selective Volume Mixup for Video Action Recognition
Yi Tan, Zhaofan Qiu, Yanbin Hao +2
The recent advances in Convolutional Neural Networks (CNNs) and Vision Transformers have convincingly demonstrated high learning capability for video action recognition on large da…
CgT-GAN: CLIP-guided Text GAN for Image Captioning
Jiarui Yu, Haoran Li, Yanbin Hao +3
The large-scale visual-language pre-trained model, Contrastive Language-Image Pre-training (CLIP), has significantly improved image captioning for scenarios without human-annotated…
Masked Collaborative Contrast for Weakly Supervised Semantic Segmentation
Fangwen Wu, Jingxuan He, Yufei Yin +3
This study introduces an efficacious approach, Masked Collaborative Contrast (MCC), to highlight semantic regions in weakly supervised semantic segmentation. MCC adroitly draws ins…
Bi-directional Distribution Alignment for Transductive Zero-Shot Learning
Zhicai Wang, Yanbin Hao, Tingting Mu +3
It is well-known that zero-shot learning (ZSL) can suffer severely from the problem of domain shift, where the true and learned data distributions for the unseen classes do not mat…
TKN: Transformer-based Keypoint Prediction Network For Real-time Video Prediction
Haoran Li, XiaoLu Li, Yihang Lin +4
Video prediction is a complex time-series forecasting task with great potential in many use cases. However, traditional methods prioritize accuracy and overlook slow prediction spe…