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20152022
most citedMake-A-Video: Text-to-Video Generation without Text-Video Data

315 citations · 955 across the 38 of their papers we have counts for

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Showing 2018 · cs.CVShow all

6 papers · 2 filters

cs.CV2018

nocaps: novel object captioning at scale

Harsh Agrawal, Karan Desai, Yufei Wang +7

Image captioning models have achieved impressive results on datasets containing limited visual concepts and large amounts of paired image-caption training data. However, if these m…

cs.CV2018

Visual Coreference Resolution in Visual Dialog using Neural Module Networks

Satwik Kottur, José M. F. Moura, Devi Parikh +2

Visual dialog entails answering a series of questions grounded in an image, using dialog history as context. In addition to the challenges found in visual question answering (VQA),…

cs.CV2018

Choose Your Neuron: Incorporating Domain Knowledge through Neuron-Importance

Ramprasaath R. Selvaraju, Prithvijit Chattopadhyay, Mohamed Elhoseiny +4

Individual neurons in convolutional neural networks supervised for image-level classification tasks have been shown to implicitly learn semantically meaningful concepts ranging fro…

cs.CV2018

Graph R-CNN for Scene Graph Generation

Jianwei Yang, Jiasen Lu, Stefan Lee +2

We propose a novel scene graph generation model called Graph R-CNN, that is both effective and efficient at detecting objects and their relations in images. Our model contains a Re…

cs.CV2018

Pythia v0.1: the Winning Entry to the VQA Challenge 2018

Yu Jiang, Vivek Natarajan, Xinlei Chen +3

This document describes Pythia v0.1, the winning entry from Facebook AI Research (FAIR)'s A-STAR team to the VQA Challenge 2018. Our starting point is a modular re-implementation o…

cs.CV2018

Neural Baby Talk

Jiasen Lu, Jianwei Yang, Dhruv Batra +1

We introduce a novel framework for image captioning that can produce natural language explicitly grounded in entities that object detectors find in the image. Our approach reconcil…