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20172021
most citedDeep Binary Reconstruction for Cross-modal Hashing

41 citations · 123 across the 9 of their papers we have counts for

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14 papers · 1 filter

cs.CV20232 cited

Robust Cross-Modal Knowledge Distillation for Unconstrained Videos

Wenke Xia, Xingjian Li, Andong Deng +3

Cross-modal distillation has been widely used to transfer knowledge across different modalities, enriching the representation of the target unimodal one. Recent studies highly rela…

cs.CV20213 cited

Cyclic Co-Learning of Sounding Object Visual Grounding and Sound Separation

Yapeng Tian, Di Hu, Chenliang Xu

There are rich synchronized audio and visual events in our daily life. Inside the events, audio scenes are associated with the corresponding visual objects; meanwhile, sounding obj…

cs.CV20203 cited

Temporal Relational Modeling with Self-Supervision for Action Segmentation

Dong Wang, Di Hu, Xingjian Li +1

Temporal relational modeling in video is essential for human action understanding, such as action recognition and action segmentation. Although Graph Convolution Networks (GCNs) ha…

cs.CV2020

Discriminative Sounding Objects Localization via Self-supervised Audiovisual Matching

Di Hu, Rui Qian, Minyue Jiang +5

Discriminatively localizing sounding objects in cocktail-party, i.e., mixed sound scenes, is commonplace for humans, but still challenging for machines. In this paper, we propose a…

cs.CV20208 cited

Multiple Sound Sources Localization from Coarse to Fine

Rui Qian, Di Hu, Heinrich Dinkel +3

How to visually localize multiple sound sources in unconstrained videos is a formidable problem, especially when lack of the pairwise sound-object annotations. To solve this proble…

cs.CV202030 cited

Ambient Sound Helps: Audiovisual Crowd Counting in Extreme Conditions

Di Hu, Lichao Mou, Qingzhong Wang +4

Visual crowd counting has been recently studied as a way to enable people counting in crowd scenes from images. Albeit successful, vision-based crowd counting approaches could fail…