most citedDynamic Gradient Reactivation for Backward Compatible Person Re-identification

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CL2023

AraMUS: Pushing the Limits of Data and Model Scale for Arabic Natural Language Processing

Asaad Alghamdi, Xinyu Duan, Wei Jiang +9

Developing monolingual large Pre-trained Language Models (PLMs) is shown to be very successful in handling different tasks in Natural Language Processing (NLP). In this work, we pr…

cs.CV2023

On Function-Coupled Watermarks for Deep Neural Networks

Xiangyu Wen, Yu Li, Wei Jiang +1

Well-performed deep neural networks (DNNs) generally require massive labelled data and computational resources for training. Various watermarking techniques are proposed to protect…

cs.CV20232 cited

MSINet: Twins Contrastive Search of Multi-Scale Interaction for Object ReID

Jianyang Gu, Kai Wang, Hao Luo +6

Neural Architecture Search (NAS) has been increasingly appealing to the society of object Re-Identification (ReID), for that task-specific architectures significantly improve the r…

cs.CV20221 cited

Dynamic Gradient Reactivation for Backward Compatible Person Re-identification

Xiao Pan, Hao Luo, Weihua Chen +6

We study the backward compatible problem for person re-identification (Re-ID), which aims to constrain the features of an updated new model to be comparable with the existing featu…

eess.IV2022

FAIVConf: Face enhancement for AI-based Video Conference with Low Bit-rate

Zhengang Li, Sheng Lin, Shan Liu +4

Recently, high-quality video conferencing with fewer transmission bits has become a very hot and challenging problem. We propose FAIVConf, a specially designed video compression fr…