activity
20092022
most citedDeepSaliency: Multi-Task Deep Neural Network Model for Salient Object Detection

571 citations · 1.9k across the 53 of their papers we have counts for

collaborators

53 papers

cs.CV2022★ 5 cited

Compositional Temporal Grounding with Structured Variational Cross-Graph Correspondence Learning

Juncheng Li, Junlin Xie, Long Qian +6

Temporal grounding in videos aims to localize one target video segment that semantically corresponds to a given query sentence. Thanks to the semantic diversity of natural language…

eess.IV2022★ 26 cited

Boosting RGB-D Saliency Detection by Leveraging Unlabeled RGB Images

Xiaoqiang Wang, Lei Zhu, Siliang Tang +5

Training deep models for RGB-D salient object detection (SOD) often requires a large number of labeled RGB-D images. However, RGB-D data is not easily acquired, which limits the de…

cs.IR2021★ 116 cited

CauseRec: Counterfactual User Sequence Synthesis for Sequential Recommendation

Shengyu Zhang, Dong Yao, Zhou Zhao +2

Learning user representations based on historical behaviors lies at the core of modern recommender systems. Recent advances in sequential recommenders have convincingly demonstrate…

cs.CV2021

Adaptive Hierarchical Graph Reasoning with Semantic Coherence for Video-and-Language Inference

Juncheng Li, Siliang Tang, Linchao Zhu +5

Video-and-Language Inference is a recently proposed task for joint video-and-language understanding. This new task requires a model to draw inference on whether a natural language…

cs.CL2021

CIL: Contrastive Instance Learning Framework for Distantly Supervised Relation Extraction

Tao Chen, Haizhou Shi, Siliang Tang +3

The journey of reducing noise from distant supervision (DS) generated training data has been started since the DS was first introduced into the relation extraction (RE) task. For t…

cs.CV2021★ 5 cited

Unsupervised Domain Adaptation for Image Classification via Structure-Conditioned Adversarial Learning

Hui Wang, Jian Tian, Songyuan Li +4

Unsupervised domain adaptation (UDA) typically carries out knowledge transfer from a label-rich source domain to an unlabeled target domain by adversarial learning. In principle, e…