activity
20162022
most citedFully Self-Supervised Learning for Semantic Segmentation

11 citations · 16 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CV20221 cited

Arbitrary Bit-width Network: A Joint Layer-Wise Quantization and Adaptive Inference Approach

Chen Tang, Haoyu Zhai, Kai Ouyang +3

Conventional model quantization methods use a fixed quantization scheme to different data samples, which ignores the inherent "recognition difficulty" differences between various s…

cs.CV20221 cited

A Closer Look at Debiased Temporal Sentence Grounding in Videos: Dataset, Metric, and Approach

Xiaohan Lan, Yitian Yuan, Xin Wang +4

Temporal Sentence Grounding in Videos (TSGV), which aims to ground a natural language sentence in an untrimmed video, has drawn widespread attention over the past few years. Howeve…

cs.CV202211 cited

Fully Self-Supervised Learning for Semantic Segmentation

Yuan Wang, Wei Zhuo, Yucong Li +3

In this work, we present a fully self-supervised framework for semantic segmentation(FS^4). A fully bootstrapped strategy for semantic segmentation, which saves efforts for the hug…

cs.CV20213 cited

A Survey on Temporal Sentence Grounding in Videos

Xiaohan Lan, Yitian Yuan, Xin Wang +2

Temporal sentence grounding in videos(TSGV), which aims to localize one target segment from an untrimmed video with respect to a given sentence query, has drawn increasing attentio…

cs.MM2021

Multimedia Edge Computing

Zhi Wang, Wenwu Zhu, Lifeng Sun +6

In this paper, we investigate the recent studies on multimedia edge computing, from sensing not only traditional visual/audio data but also individuals' geographical preference and…

cs.CE2020

STSIR: Spatial Temporal Pandemic Model with Mobility Data

Wang Pan, Qipu Deng, Jiadong Li +2

With the outbreak of COVID-19, how to mitigate and suppress its spread is a big issue to the government. Department of public health need powerful models to model and predict the t…