activity
20182022
most citedFederated Mutual Learning

71 citations · 163 across the 26 of their papers we have counts for

collaborators

45 papers

cs.CL20221 cited

End-to-end contextual asr based on posterior distribution adaptation for hybrid ctc/attention system

Zhengyi Zhang, Pan Zhou

End-to-end (E2E) speech recognition architectures assemble all components of traditional speech recognition system into a single model. Although it simplifies ASR system, it introd…

cs.CV2022

Exploring Motion and Appearance Information for Temporal Sentence Grounding

Daizong Liu, Xiaoye Qu, Pan Zhou +1

This paper addresses temporal sentence grounding. Previous works typically solve this task by learning frame-level video features and align them with the textual information. A maj…

cs.CL2021

Wav-BERT: Cooperative Acoustic and Linguistic Representation Learning for Low-Resource Speech Recognition

Guolin Zheng, Yubei Xiao, Ke Gong +3

Unifying acoustic and linguistic representation learning has become increasingly crucial to transfer the knowledge learned on the abundance of high-resource language data for low-r…

cs.CV2021

Progressively Guide to Attend: An Iterative Alignment Framework for Temporal Sentence Grounding

Daizong Liu, Xiaoye Qu, Pan Zhou

A key solution to temporal sentence grounding (TSG) exists in how to learn effective alignment between vision and language features extracted from an untrimmed video and a sentence…

cs.CV2021

Adaptive Proposal Generation Network for Temporal Sentence Localization in Videos

Daizong Liu, Xiaoye Qu, Jianfeng Dong +1

We address the problem of temporal sentence localization in videos (TSLV). Traditional methods follow a top-down framework which localizes the target segment with pre-defined segme…

cs.CV20213 cited

Coarse to Fine: Domain Adaptive Crowd Counting via Adversarial Scoring Network

Zhikang Zou, Xiaoye Qu, Pan Zhou +4

Recent deep networks have convincingly demonstrated high capability in crowd counting, which is a critical task attracting widespread attention due to its various industrial applic…