research
∙
12/16/2021
SGEITL: Scene Graph Enhanced Image-Text Learning for Visual Commonsense Reasoning
Answering complex questions about images is an ambitious goal for machin...
share
research
∙
11/20/2020
Open-Vocabulary Object Detection Using Captions
Despite the remarkable accuracy of deep neural networks in object detect...
research
∙
10/24/2020
Weakly-supervised VisualBERT: Pre-training without Parallel Images and Captions
Pre-trained contextual vision-and-language (V L) models have brought i...
research
∙
06/17/2020
Learning Visual Commonsense for Robust Scene Graph Generation
Scene graph generation models understand the scene through object and pr...
research
∙
05/05/2020
Cross-media Structured Common Space for Multimedia Event Extraction
We introduce a new task, MultiMedia Event Extraction (M2E2), which aims ...
research
∙
01/08/2020
Weakly Supervised Visual Semantic Parsing
Scene Graph Generation (SGG) aims to extract entities, predicates and th...
research
∙
01/07/2020
Bridging Knowledge Graphs to Generate Scene Graphs
Scene graphs are powerful representations that encode images into their ...
research
∙
01/05/2020
General Partial Label Learning via Dual Bipartite Graph Autoencoder
We formulate a practical yet challenging problem: General Partial Label ...
research
∙
05/23/2019
CDSA: Cross-Dimensional Self-Attention for Multivariate, Geo-tagged Time Series Imputation
Many real-world applications involve multivariate, geo-tagged time serie...
research
∙
10/27/2018
Low-shot Learning via Covariance-Preserving Adversarial Augmentation Networks
Deep neural networks suffer from over-fitting and catastrophic forgettin...
research
∙
03/04/2017
