15 citations · 28 across the 8 of their papers we have counts for
8 papers
LocFormer: Enabling Transformers to Perform Temporal Moment Localization on Long Untrimmed Videos With a Feature Sampling Approach
Cristian Rodriguez-Opazo, Edison Marrese-Taylor, Basura Fernando +2
We propose LocFormer, a Transformer-based model for video grounding which operates at a constant memory footprint regardless of the video length, i.e. number of frames. LocFormer i…
Adaptive Mimic: Deep Reinforcement Learning of Parameterized Bipedal Walking from Infeasible References
Chong Zhang, Qi Wu, Liqian Ma +1
Not until recently, robust robot locomotion has been achieved by deep reinforcement learning (DRL). However, for efficient learning of parametrized bipedal walking, developed refer…
Memory Regulation and Alignment toward Generalizer RGB-Infrared Person
Feng Chen, Fei Wu, Qi Wu +1
The domain shift, coming from unneglectable modality gap and non-overlapped identity classes between training and test sets, is a major issue of RGB-Infrared person re-identificati…
Data-driven advice for interpreting local and global model predictions in bioinformatics problems
Markus Loecher, Qi Wu
Tree-based algorithms such as random forests and gradient boosted trees continue to be among the most popular and powerful machine learning models used across multiple disciplines.…
Data Hiding with Deep Learning: A Survey Unifying Digital Watermarking and Steganography
Zihan Wang, Olivia Byrnes, Hu Wang +5
The advancement of secure communication and identity verification fields has significantly increased through the use of deep learning techniques for data hiding. By embedding infor…
Multi-intersection Traffic Optimisation: A Benchmark Dataset and a Strong Baseline
Hu Wang, Hao Chen, Qi Wu +3
The control of traffic signals is fundamental and critical to alleviate traffic congestion in urban areas. However, it is challenging since traffic dynamics are complicated in real…
Memory-Gated Recurrent Networks
Yaquan Zhang, Qi Wu, Nanbo Peng +3
The essence of multivariate sequential learning is all about how to extract dependencies in data. These data sets, such as hourly medical records in intensive care units and multi-…
Quantized Adam with Error Feedback
Congliang Chen, Li Shen, Haozhi Huang +1
In this paper, we present a distributed variant of adaptive stochastic gradient method for training deep neural networks in the parameter-server model. To reduce the communication…