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Found 8 papers, 3 papers with code
Visible Watermark Removal via Self-calibrated Localization and Background Refinement
In the refinement stage, we integrate multi-level features to improve the texture quality of watermarked area.
Joint Optimization for Coordinated Charging Control of Commercial Electric Vehicles Under Distributed Hydrogen Energy Supply
The transition to the zero-carbon power system is underway accelerating recently.
Searching for Actions on the Hyperbole
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.
On Posterior Collapse and Encoder Feature Dispersion in Sequence VAEs
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.
A Cross-Domain Transferable Neural Coherence Model
Coherence is an important aspect of text quality and is crucial for ensuring its readability.
World Knowledge for Reading Comprehension: Rare Entity Prediction with Hierarchical LSTMs Using External Descriptions
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.
Radial Velocity Retrieval for Multichannel SAR Moving Targets with Time-Space Doppler De-ambiguity
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
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.
