580 citations · 3.8k across the 56 of their papers we have counts for
8 papers · 2 filters
12-in-1: Multi-Task Vision and Language Representation Learning
Jiasen Lu, Vedanuj Goswami, Marcus Rohrbach +2
Much of vision-and-language research focuses on a small but diverse set of independent tasks and supporting datasets often studied in isolation; however, the visually-grounded lang…
Iterative Answer Prediction with Pointer-Augmented Multimodal Transformers for TextVQA
Ronghang Hu, Amanpreet Singh, Trevor Darrell +1
Many visual scenes contain text that carries crucial information, and it is thus essential to understand text in images for downstream reasoning tasks. For example, a deep water la…
Decoupling Representation and Classifier for Long-Tailed Recognition
Bingyi Kang, Saining Xie, Marcus Rohrbach +4
The long-tail distribution of the visual world poses great challenges for deep learning based classification models on how to handle the class imbalance problem. Existing solutions…
Learning to Generate Grounded Visual Captions without Localization Supervision
Chih-Yao Ma, Yannis Kalantidis, Ghassan AlRegib +3
When automatically generating a sentence description for an image or video, it often remains unclear how well the generated caption is grounded, that is whether the model uses the…
Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution
Yunpeng Chen, Haoqi Fan, Bing Xu +5
In natural images, information is conveyed at different frequencies where higher frequencies are usually encoded with fine details and lower frequencies are usually encoded with gl…
CLEVR-Dialog: A Diagnostic Dataset for Multi-Round Reasoning in Visual Dialog
Satwik Kottur, José M. F. Moura, Devi Parikh +2
Visual Dialog is a multimodal task of answering a sequence of questions grounded in an image, using the conversation history as context. It entails challenges in vision, language,…