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20152026
most citedVisual Saliency Based on Multiscale Deep Features

259 citations · 590 across the 60 of their papers we have counts for

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Showing 2020Show all

15 papers · 1 filter

cs.CV20208 cited

Cross-Modal Collaborative Representation Learning and a Large-Scale RGBT Benchmark for Crowd Counting

Lingbo Liu, Jiaqi Chen, Hefeng Wu +3

Crowd counting is a fundamental yet challenging task, which desires rich information to generate pixel-wise crowd density maps. However, most previous methods only used the limited…

cs.CV2020

Human-centric Spatio-Temporal Video Grounding With Visual Transformers

Zongheng Tang, Yue Liao, Si Liu +5

In this work, we introduce a novel task - Humancentric Spatio-Temporal Video Grounding (HC-STVG). Unlike the existing referring expression tasks in images or videos, by focusing on…

cs.CV2020

A Hamiltonian Monte Carlo Method for Probabilistic Adversarial Attack and Learning

Hongjun Wang, Guanbin Li, Xiaobai Liu +1

Although deep convolutional neural networks (CNNs) have demonstrated remarkable performance on multiple computer vision tasks, researches on adversarial learning have shown that de…

eess.IV2020

Contralaterally Enhanced Networks for Thoracic Disease Detection

Gangming Zhao, Chaowei Fang, Guanbin Li +2

Identifying and locating diseases in chest X-rays are very challenging, due to the low visual contrast between normal and abnormal regions, and distortions caused by other overlapp…

cs.CV202010 cited

Linguistic Structure Guided Context Modeling for Referring Image Segmentation

Tianrui Hui, Si Liu, Shaofei Huang +4

Referring image segmentation aims to predict the foreground mask of the object referred by a natural language sentence. Multimodal context of the sentence is crucial to distinguish…

cs.CV20203 cited

Referring Image Segmentation via Cross-Modal Progressive Comprehension

Shaofei Huang, Tianrui Hui, Si Liu +5

Referring image segmentation aims at segmenting the foreground masks of the entities that can well match the description given in the natural language expression. Previous approach…