activity
20172022
most citedContextual Non-Local Alignment over Full-Scale Representation for Text-Based Person Search

61 citations · 77 across the 5 of their papers we have counts for

collaborators
Showing cs.CVShow all

6 papers · 1 filter

cs.CV2021

PR-Net: Preference Reasoning for Personalized Video Highlight Detection

Runnan Chen, Penghao Zhou, Wenzhe Wang +4

Personalized video highlight detection aims to shorten a long video to interesting moments according to a user's preference, which has recently raised the community's attention. Cu…

cs.CV2021

Ask&Confirm: Active Detail Enriching for Cross-Modal Retrieval with Partial Query

Guanyu Cai, Jun Zhang, Xinyang Jiang +7

Text-based image retrieval has seen considerable progress in recent years. However, the performance of existing methods suffers in real life since the user is likely to provide an…

cs.CV202161 cited

Contextual Non-Local Alignment over Full-Scale Representation for Text-Based Person Search

Chenyang Gao, Guanyu Cai, Xinyang Jiang +6

Text-based person search aims at retrieving target person in an image gallery using a descriptive sentence of that person. It is very challenging since modal gap makes effectively…

cs.CV2021

Global2Local: Efficient Structure Search for Video Action Segmentation

Shang-Hua Gao, Qi Han, Zhong-Yu Li +3

Temporal receptive fields of models play an important role in action segmentation. Large receptive fields facilitate the long-term relations among video clips while small receptive…

cs.CV20204 cited

NOH-NMS: Improving Pedestrian Detection by Nearby Objects Hallucination

Penghao Zhou, Chong Zhou, Pai Peng +4

Greedy-NMS inherently raises a dilemma, where a lower NMS threshold will potentially lead to a lower recall rate and a higher threshold introduces more false positives. This proble…

cs.CV201711 cited

Deep Co-Space: Sample Mining Across Feature Transformation for Semi-Supervised Learning

Ziliang Chen, Keze Wang, Xiao Wang +3

Aiming at improving performance of visual classification in a cost-effective manner, this paper proposes an incremental semi-supervised learning paradigm called Deep Co-Space (DCS)…