Search Results for author: Teng Long

Found 8 papers, 3 papers with code

Visible Watermark Removal via Self-calibrated Localization and Background Refinement

1 code implementation8 Aug 2021 Jing Liang, Li Niu, Fengjun Guo, Teng Long, Liqing Zhang

In the refinement stage, we integrate multi-level features to improve the texture quality of watermarked area.

Multi-Task Learning

Searching for Actions on the Hyperbole

1 code implementation CVPR 2020 Teng Long, Pascal Mettes, Heng Tao Shen, Cees G. M. Snoek

Starting from the observation that hierarchies are mostly ignored in the action literature, we retrieve not only individual actions but also relevant and related actions, given an action name or video example as input.

Action Recognition Video Retrieval +1

On Posterior Collapse and Encoder Feature Dispersion in Sequence VAEs

no code implementations10 Nov 2019 Teng Long, Yanshuai Cao, Jackie Chi Kit Cheung

Variational autoencoders (VAEs) hold great potential for modelling text, as they could in theory separate high-level semantic and syntactic properties from local regularities of natural language.

Language Modelling

World Knowledge for Reading Comprehension: Rare Entity Prediction with Hierarchical LSTMs Using External Descriptions

no code implementations EMNLP 2017 Teng Long, Emmanuel Bengio, Ryan Lowe, Jackie Chi Kit Cheung, Doina Precup

Humans interpret texts with respect to some background information, or world knowledge, and we would like to develop automatic reading comprehension systems that can do the same.

Language Modelling Reading Comprehension

Radial Velocity Retrieval for Multichannel SAR Moving Targets with Time-Space Doppler De-ambiguity

no code implementations1 Oct 2016 Jia Xu, Zu-Zhen Huang, Zhi-Rui Wang, Li Xiao, Xiang-Gen Xia, Teng Long

Accordingly, the multichannel SAR systems with different parameters are investigated in three different cases with diverse Doppler ambiguity properties, and a multi-frequency SAR is then proposed to obtain the RV estimation by solving the ambiguity problem based on Chinese remainder theorem (CRT).

Leveraging Lexical Resources for Learning Entity Embeddings in Multi-Relational Data

no code implementations ACL 2016 Teng Long, Ryan Lowe, Jackie Chi Kit Cheung, Doina Precup

Recent work in learning vector-space embeddings for multi-relational data has focused on combining relational information derived from knowledge bases with distributional information derived from large text corpora.

Entity Embeddings

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