32 citations · 44 across the 5 of their papers we have counts for
9 papers
Learning Audio-Visual embedding for Person Verification in the Wild
Peiwen Sun, Shanshan Zhang, Zishan Liu +4
It has already been observed that audio-visual embedding is more robust than uni-modality embedding for person verification. Here, we proposed a novel audio-visual strategy that co…
RePre: Improving Self-Supervised Vision Transformer with Reconstructive Pre-training
Luya Wang, Feng Liang, Yangguang Li +3
Recently, self-supervised vision transformers have attracted unprecedented attention for their impressive representation learning ability. However, the dominant method, contrastive…
Deep Sketch-Based Modeling: Tips and Tricks
Yue Zhong, Yulia Gryaditskaya, Honggang Zhang +1
Deep image-based modeling received lots of attention in recent years, yet the parallel problem of sketch-based modeling has only been briefly studied, often as a potential applicat…
Adaptive convolutional neural networks for k-space data interpolation in fast magnetic resonance imaging
Tianming Du, Honggang Zhang, Yuemeng Li +2
Deep learning in k-space has demonstrated great potential for image reconstruction from undersampled k-space data in fast magnetic resonance imaging (MRI). However, existing deep l…
Self-Supervised Convolutional Subspace Clustering Network
Junjian Zhang, Chun-Guang Li, Chong You +4
Subspace clustering methods based on data self-expression have become very popular for learning from data that lie in a union of low-dimensional linear subspaces. However, the appl…
Deep Attentive Tracking via Reciprocative Learning
Shi Pu, Yibing Song, Chao Ma +2
Visual attention, derived from cognitive neuroscience, facilitates human perception on the most pertinent subset of the sensory data. Recently, significant efforts have been made t…