241 citations · 957 across the 29 of their papers we have counts for
10 papers · 1 filter
Unsupervised Few-shot Learning via Self-supervised Training
Zilong Ji, Xiaolong Zou, Tiejun Huang +1
Learning from limited exemplars (few-shot learning) is a fundamental, unsolved problem that has been laboriously explored in the machine learning community. However, current few-sh…
An Efficient Coding Method for Spike Camera using Inter-Spike Intervals
Siwei Dong, Lin Zhu, Daoyuan Xu +2
Recently, a novel bio-inspired spike camera has been proposed, which continuously accumulates luminance intensity and fires spikes while the dispatch threshold is reached. Compared…
Transductive Episodic-Wise Adaptive Metric for Few-Shot Learning
Limeng Qiao, Yemin Shi, Jia Li +3
Few-shot learning, which aims at extracting new concepts rapidly from extremely few examples of novel classes, has been featured into the meta-learning paradigm recently. Yet, the…
Global-Local Temporal Representations For Video Person Re-Identification
Jianing Li, Jingdong Wang, Qi Tian +2
This paper proposes the Global-Local Temporal Representation (GLTR) to exploit the multi-scale temporal cues in video sequences for video person Re-Identification (ReID). GLTR is c…
Spatiotemporal Information Processing with a Reservoir Decision-making Network
Yuanyuan Mi, Xiaohan Lin, Xiaolong Zou +3
Spatiotemporal information processing is fundamental to brain functions. The present study investigates a canonic neural network model for spatiotemporal pattern recognition. Speci…
A Retina-inspired Sampling Method for Visual Texture Reconstruction
Lin Zhu, Siwei Dong, Tiejun Huang +1
Conventional frame-based camera is not able to meet the demand of rapid reaction for real-time applications, while the emerging dynamic vision sensor (DVS) can realize high speed c…