activity
20192023
most citedRefSAM: Efficiently Adapting Segmenting Anything Model for Referring Video Object Segmentation

7 citations · 12 across the 4 of their papers we have counts for

collaborators

6 papers

cs.RO2023

Learning a Stable Dynamic System with a Lyapunov Energy Function for Demonstratives Using Neural Networks

Yu Zhang, Yongxiang Zou, Haoyu Zhang +2

Autonomous Dynamic System (DS)-based algorithms hold a pivotal and foundational role in the field of Learning from Demonstration (LfD). Nevertheless, they confront the formidable c…

cs.CV2023★ 7 cited

RefSAM: Efficiently Adapting Segmenting Anything Model for Referring Video Object Segmentation

Yonglin Li, Jing Zhang, Xiao Teng +2

The Segment Anything Model (SAM) has gained significant attention for its impressive performance in image segmentation. However, it lacks proficiency in referring video object segm…

cs.RO2023

Learning Variable Impedance Skills from Demonstrations with Passivity Guarantee

Yu Zhang, Long Cheng, Xiuze Xia +1

Robots are increasingly being deployed not only in workplaces but also in households. Effectively execute of manipulation tasks by robots relies on variable impedance control with…

eess.IV2022★ 5 cited

Temporally and Spatially variant-resolution illumination patterns in computational ghost imaging

Dong Zhou, Jie Cao, Huan Cui +4

Conventional computational ghost imaging (CGI) uses light carrying a sequence of patterns with uniform-resolution to illuminate the object, then performs correlation calculation ba…

cs.CL2020

Keyphrase Extraction with Dynamic Graph Convolutional Networks and Diversified Inference

Haoyu Zhang, Dingkun Long, Guangwei Xu +3

Keyphrase extraction (KE) aims to summarize a set of phrases that accurately express a concept or a topic covered in a given document. Recently, Sequence-to-Sequence (Seq2Seq) base…

cs.CL2019

Pretraining-Based Natural Language Generation for Text Summarization

Haoyu Zhang, Jianjun Xu, Ji Wang

In this paper, we propose a novel pretraining-based encoder-decoder framework, which can generate the output sequence based on the input sequence in a two-stage manner. For the enc…