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Found 11 papers, 5 papers with code
OpenSUN3D: 1st Workshop Challenge on Open-Vocabulary 3D Scene Understanding
This report provides an overview of the challenge hosted at the OpenSUN3D Workshop on Open-Vocabulary 3D Scene Understanding held in conjunction with ICCV 2023.
An Unobtrusive and Lightweight Ear-worn System for Continuous Epileptic Seizure Detection
Epilepsy is one of the most common neurological diseases globally, affecting around 50 million people worldwide.
$\textit{greylock}$: A Python Package for Measuring The Composition of Complex Datasets
However, there exists a richer and potentially more useful set of measures, termed diversity measures, that incorporate elements' frequencies and between-element similarities.
Real-Time Diagnostic Integrity Meets Efficiency: A Novel Platform-Agnostic Architecture for Physiological Signal Compression
Head-based signals such as EEG, EMG, EOG, and ECG collected by wearable systems will play a pivotal role in clinical diagnosis, monitoring, and treatment of important brain disorder diseases.
TabIQA: Table Questions Answering on Business Document Images
Table answering questions from business documents has many challenges that require understanding tabular structures, cross-document referencing, and additional numeric computations beyond simple search queries.
Rethinking Image-based Table Recognition Using Weakly Supervised Methods
In this paper, we propose a weakly supervised model named WSTabNet for table recognition that relies only on HTML (or LaTeX) code-level annotations of table images.
TabEAno: Table to Knowledge Graph Entity Annotation
In the Open Data era, a large number of table resources have been made available on the Web and data portals.
MTab: Matching Tabular Data to Knowledge Graph using Probability Models
This paper presents the design of our system, namely MTab, for Semantic Web Challenge on Tabular Data to Knowledge Graph Matching (SemTab 2019).
Active Testing: An Efficient and Robust Framework for Estimating Accuracy
Much recent work on visual recognition aims to scale up learning to massive, noisily-annotated datasets.
EmbNum: Semantic labeling for numerical values with deep metric learning
Semantic labeling for numerical values is a task of assigning semantic labels to unknown numerical attributes.
Weakly Supervised Action Localization by Sparse Temporal Pooling Network
We propose a weakly supervised temporal action localization algorithm on untrimmed videos using convolutional neural networks.
Ranked #13 on
Weakly Supervised Action Localization
on ActivityNet-1.3
(mAP@0.5 metric)
