activity
20182023
most citedLocal-Global Context Aware Transformer for Language-Guided Video Segmentation

105 citations · 249 across the 12 of their papers we have counts for

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Showing 2021Show all

6 papers · 1 filter

cs.SD2021

Multi-Channel Far-Field Speaker Verification with Large-Scale Ad-hoc Microphone Arrays

Chengdong Liang, Yijiang Chen, Jiadi Yao +1

Speaker verification based on ad-hoc microphone arrays has the potential of reducing the error significantly in adverse acoustic environments. However, existing approaches extract…

cs.CV2021★ 1 cited

Contrastive Video-Language Segmentation

Chen Liang, Yawei Luo, Yu Wu +1

We focus on the problem of segmenting a certain object referred by a natural language sentence in video content, at the core of formulating a pinpoint vision-language relation. Whi…

cs.CV2021★ 32 cited

Rethinking Cross-modal Interaction from a Top-down Perspective for Referring Video Object Segmentation

Chen Liang, Yu Wu, Tianfei Zhou +4

Referring video object segmentation (RVOS) aims to segment video objects with the guidance of natural language reference. Previous methods typically tackle RVOS through directly gr…

eess.AS2021★ 8 cited

Libri-adhoc40: A dataset collected from synchronized ad-hoc microphone arrays

Shanzheng Guan, Shupei Liu, Junqi Chen +8

Recently, there is a research trend on ad-hoc microphone arrays. However, most research was conducted on simulated data. Although some data sets were collected with a small number…

cs.SD2021★ 2 cited

Transformer-based end-to-end speech recognition with residual Gaussian-based self-attention

Chengdong Liang, Menglong Xu, Xiao-Lei Zhang

Self-attention (SA), which encodes vector sequences according to their pairwise similarity, is widely used in speech recognition due to its strong context modeling ability. However…

cs.CV2021★ 20 cited

ClawCraneNet: Leveraging Object-level Relation for Text-based Video Segmentation

Chen Liang, Yu Wu, Yawei Luo +1

Text-based video segmentation is a challenging task that segments out the natural language referred objects in videos. It essentially requires semantic comprehension and fine-grain…