73 citations · 241 across the 38 of their papers we have counts for
8 papers · 1 filter
STSC-SNN: Spatio-Temporal Synaptic Connection with Temporal Convolution and Attention for Spiking Neural Networks
Chengting Yu, Zheming Gu, Da Li +3
Spiking Neural Networks (SNNs), as one of the algorithmic models in neuromorphic computing, have gained a great deal of research attention owing to temporal information processing…
Missing Modality meets Meta Sampling (M3S): An Efficient Universal Approach for Multimodal Sentiment Analysis with Missing Modality
Haozhe Chi, Minghua Yang, Junhao Zhu +2
Multimodal sentiment analysis (MSA) is an important way of observing mental activities with the help of data captured from multiple modalities. However, due to the recording or tra…
Hierarchical Semi-Supervised Contrastive Learning for Contamination-Resistant Anomaly Detection
Gaoang Wang, Yibing Zhan, Xinchao Wang +2
Anomaly detection aims at identifying deviant samples from the normal data distribution. Contrastive learning has provided a successful way to sample representation that enables ef…
Recent Advances in Embedding Methods for Multi-Object Tracking: A Survey
Gaoang Wang, Mingli Song, Jenq-Neng Hwang
Multi-object tracking (MOT) aims to associate target objects across video frames in order to obtain entire moving trajectories. With the advancement of deep neural networks and the…
Preserve Pre-trained Knowledge: Transfer Learning With Self-Distillation For Action Recognition
Yang Zhou, Zhanhao He, Keyu Lu +2
Video-based action recognition is one of the most popular topics in computer vision. With recent advances of selfsupervised video representation learning approaches, action recogni…
Human-Centered Prior-Guided and Task-Dependent Multi-Task Representation Learning for Action Recognition Pre-Training
Guanhong Wang, Keyu Lu, Yang Zhou +2
Recently, much progress has been made for self-supervised action recognition. Most existing approaches emphasize the contrastive relations among videos, including appearance and mo…
MAP-SNN: Mapping Spike Activities with Multiplicity, Adaptability, and Plasticity into Bio-Plausible Spiking Neural Networks
Chengting Yu, Yangkai Du, Mufeng Chen +3
Spiking Neural Network (SNN) is considered more biologically realistic and power-efficient as it imitates the fundamental mechanism of the human brain. Recently, backpropagation (B…
Self-paced Multi-grained Cross-modal Interaction Modeling for Referring Expression Comprehension
Peihan Miao, Wei Su, Gaoang Wang +2
As an important and challenging problem in vision-language tasks, referring expression comprehension (REC) generally requires a large amount of multi-grained information of visual…