538 citations · 2.4k across the 71 of their papers we have counts for
14 papers · 1 filter
Weakly-Supervised Video Moment Retrieval via Semantic Completion Network
Zhijie Lin, Zhou Zhao, Zhu Zhang +2
Video moment retrieval is to search the moment that is most relevant to the given natural language query. Existing methods are mostly trained in a fully-supervised setting, which r…
Multi-Modal Attention Network Learning for Semantic Source Code Retrieval
Yao Wan, Jingdong Shu, Yulei Sui +4
Code retrieval techniques and tools have been playing a key role in facilitating software developers to retrieve existing code fragments from available open-source repositories giv…
A Better Way to Attend: Attention with Trees for Video Question Answering
Hongyang Xue, Wenqing Chu, Zhou Zhao +1
We propose a new attention model for video question answering. The main idea of the attention models is to locate on the most informative parts of the visual data. The attention me…
Personalized Hashtag Recommendation for Micro-videos
Yinwei Wei, Zhiyong Cheng, Xuzheng Yu +3
Personalized hashtag recommendation methods aim to suggest users hashtags to annotate, categorize, and describe their posts. The hashtags, that a user provides to a post (e.g., a m…
Cross-Modal Interaction Networks for Query-Based Moment Retrieval in Videos
Zhu Zhang, Zhijie Lin, Zhou Zhao +1
Query-based moment retrieval aims to localize the most relevant moment in an untrimmed video according to the given natural language query. Existing works often only focus on one a…
MacNet: Transferring Knowledge from Machine Comprehension to Sequence-to-Sequence Models
Boyuan Pan, Yazheng Yang, Hao Li +4
Machine Comprehension (MC) is one of the core problems in natural language processing, requiring both understanding of the natural language and knowledge about the world. Rapid pro…
Discourse Marker Augmented Network with Reinforcement Learning for Natural Language Inference
Boyuan Pan, Yazheng Yang, Zhou Zhao +3
Natural Language Inference (NLI), also known as Recognizing Textual Entailment (RTE), is one of the most important problems in natural language processing. It requires to infer the…
Weak Supervision Enhanced Generative Network for Question Generation
Yutong Wang, Jiyuan Zheng, Qijiong Liu +3
Automatic question generation according to an answer within the given passage is useful for many applications, such as question answering system, dialogue system, etc. Current neur…
Localizing Unseen Activities in Video via Image Query
Zhu Zhang, Zhou Zhao, Zhijie Lin +2
Action localization in untrimmed videos is an important topic in the field of video understanding. However, existing action localization methods are restricted to a pre-defined set…
Open-Ended Long-Form Video Question Answering via Hierarchical Convolutional Self-Attention Networks
Zhu Zhang, Zhou Zhao, Zhijie Lin +2
Open-ended video question answering aims to automatically generate the natural-language answer from referenced video contents according to the given question. Currently, most exist…
ActivityNet-QA: A Dataset for Understanding Complex Web Videos via Question Answering
Zhou Yu, Dejing Xu, Jun Yu +4
Recent developments in modeling language and vision have been successfully applied to image question answering. It is both crucial and natural to extend this research direction to…
Beyond Product Quantization: Deep Progressive Quantization for Image Retrieval
Lianli Gao, Xiaosu Zhu, Jingkuan Song +2
Product Quantization (PQ) has long been a mainstream for generating an exponentially large codebook at very low memory/time cost. Despite its success, PQ is still tricky for the de…
Almost Unsupervised Text to Speech and Automatic Speech Recognition
Yi Ren, Xu Tan, Tao Qin +3
Text to speech (TTS) and automatic speech recognition (ASR) are two dual tasks in speech processing and both achieve impressive performance thanks to the recent advance in deep lea…
Multilingual Neural Machine Translation with Knowledge Distillation
Xu Tan, Yi Ren, Di He +3
Multilingual machine translation, which translates multiple languages with a single model, has attracted much attention due to its efficiency of offline training and online serving…