11 citations · 18 across the 4 of their papers we have counts for
5 papers · 1 filter
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…
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…
Grounded and Controllable Image Completion by Incorporating Lexical Semantics
Shengyu Zhang, Tan Jiang, Qinghao Huang +7
In this paper, we present an approach, namely Lexical Semantic Image Completion (LSIC), that may have potential applications in art, design, and heritage conservation, among severa…
Attentive Sequence to Sequence Translation for Localizing Clips of Interest by Natural Language Descriptions
Ke Ning, Linchao Zhu, Ming Cai +3
We propose a novel attentive sequence to sequence translator (ASST) for clip localization in videos by natural language descriptions. We make two contributions. First, we propose a…
An End-to-End Approach to Natural Language Object Retrieval via Context-Aware Deep Reinforcement Learning
Fan Wu, Zhongwen Xu, Yi Yang
We propose an end-to-end approach to the natural language object retrieval task, which localizes an object within an image according to a natural language description, i.e., referr…