activity
20192026
most citedReading-strategy Inspired Visual Representation Learning for Text-to-Video Retrieval

78 citations · 178 across the 30 of their papers we have counts for

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Showing 2021Show all

8 papers · 1 filter

cs.CL2021

Efficient Document-level Event Extraction via Pseudo-Trigger-aware Pruned Complete Graph

Tong Zhu, Xiaoye Qu, Wenliang Chen +4

Most previous studies of document-level event extraction mainly focus on building argument chains in an autoregressive way, which achieves a certain success but is inefficient in b…

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.CV2021★ 3 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…

cs.CV2021★ 15 cited

Context-aware Biaffine Localizing Network for Temporal Sentence Grounding

Daizong Liu, Xiaoye Qu, Jianfeng Dong +5

This paper addresses the problem of temporal sentence grounding (TSG), which aims to identify the temporal boundary of a specific segment from an untrimmed video by a sentence quer…

cs.CV2021★ 1 cited

Hierarchical Similarity Learning for Language-based Product Image Retrieval

Zhe Ma, Fenghao Liu, Jianfeng Dong +3

This paper aims for the language-based product image retrieval task. The majority of previous works have made significant progress by designing network structure, similarity measur…