Vision-language pre-training: Basics, recent advances, and future trends
This monograph surveys vision-language pre-training (VLP) methods for multimodal
intelligence that have been developed in the last few years. We group these approaches …
intelligence that have been developed in the last few years. We group these approaches …
A survey on causal inference
Causal inference is a critical research topic across many domains, such as statistics,
computer science, education, public policy, and economics, for decades. Nowadays …
computer science, education, public policy, and economics, for decades. Nowadays …
Graph neural networks: foundation, frontiers and applications
The field of graph neural networks (GNNs) has seen rapid and incredible strides over the
recent years. Graph neural networks, also known as deep learning on graphs, graph …
recent years. Graph neural networks, also known as deep learning on graphs, graph …
Just ask: Learning to answer questions from millions of narrated videos
Recent methods for visual question answering rely on large-scale annotated datasets.
Manual annotation of questions and answers for videos, however, is tedious, expensive and …
Manual annotation of questions and answers for videos, however, is tedious, expensive and …
Lxmert: Learning cross-modality encoder representations from transformers
Vision-and-language reasoning requires an understanding of visual concepts, language
semantics, and, most importantly, the alignment and relationships between these two …
semantics, and, most importantly, the alignment and relationships between these two …
Large-scale adversarial training for vision-and-language representation learning
We present VILLA, the first known effort on large-scale adversarial training for vision-and-
language (V+ L) representation learning. VILLA consists of two training stages:(i) task …
language (V+ L) representation learning. VILLA consists of two training stages:(i) task …
Breaking the dilemma of medical image-to-image translation
L Kong, C Lian, D Huang, Y Hu… - Advances in Neural …, 2021 - proceedings.neurips.cc
Abstract Supervised Pix2Pix and unsupervised Cycle-consistency are two modes that
dominate the field of medical image-to-image translation. However, neither modes are ideal …
dominate the field of medical image-to-image translation. However, neither modes are ideal …
Counterfactual samples synthesizing for robust visual question answering
Abstract Despite Visual Question Answering (VQA) has realized impressive progress over
the last few years, today's VQA models tend to capture superficial linguistic correlations in …
the last few years, today's VQA models tend to capture superficial linguistic correlations in …
Multimodal intelligence: Representation learning, information fusion, and applications
Deep learning methods haverevolutionized speech recognition, image recognition, and
natural language processing since 2010. Each of these tasks involves a single modality in …
natural language processing since 2010. Each of these tasks involves a single modality in …
Coot: Cooperative hierarchical transformer for video-text representation learning
Many real-world video-text tasks involve different levels of granularity, such as frames and
words, clip and sentences or videos and paragraphs, each with distinct semantics. In this …
words, clip and sentences or videos and paragraphs, each with distinct semantics. In this …