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20202022
most citedTracking Instances as Queries

6 citations · 13 across the 4 of their papers we have counts for

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6 papers · 1 filter

cs.CV2022

Robust Human Matting via Semantic Guidance

Xiangguang Chen, Ye Zhu, Yu Li +4

Automatic human matting is highly desired for many real applications. We investigate recent human matting methods and show that common bad cases happen when semantic human segmenta…

cs.CV20222 cited

Temporally Efficient Vision Transformer for Video Instance Segmentation

Shusheng Yang, Xinggang Wang, Yu Li +5

Recently vision transformer has achieved tremendous success on image-level visual recognition tasks. To effectively and efficiently model the crucial temporal information within a…

cs.CV20216 cited

Tracking Instances as Queries

Shusheng Yang, Yuxin Fang, Xinggang Wang +4

Recently, query based deep networks catch lots of attention owing to their end-to-end pipeline and competitive results on several fundamental computer vision tasks, such as object…

cs.CV2021

Instances as Queries

Yuxin Fang, Shusheng Yang, Xinggang Wang +5

Recently, query based object detection frameworks achieve comparable performance with previous state-of-the-art object detectors. However, how to fully leverage such frameworks to…

cs.CV2021

Towards Real-World Blind Face Restoration with Generative Facial Prior

Xintao Wang, Yu Li, Honglun Zhang +1

Blind face restoration usually relies on facial priors, such as facial geometry prior or reference prior, to restore realistic and faithful details. However, very low-quality input…

cs.CV20205 cited

A Simple Yet Effective Method for Video Temporal Grounding with Cross-Modality Attention

Binjie Zhang, Yu Li, Chun Yuan +3

The task of language-guided video temporal grounding is to localize the particular video clip corresponding to a query sentence in an untrimmed video. Though progress has been made…