activity
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 2019Show all

28 papers · 1 filter

cs.LG2019

Large-scale Pretraining for Visual Dialog: A Simple State-of-the-Art Baseline

Vishvak Murahari, Dhruv Batra, Devi Parikh +1

Prior work in visual dialog has focused on training deep neural models on VisDial in isolation. Instead, we present an approach to leverage pretraining on related vision-language d…

cs.CV2019

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…

cs.CV201936 cited

DD-PPO: Learning Near-Perfect PointGoal Navigators from 2.5 Billion Frames

Erik Wijmans, Abhishek Kadian, Ari Morcos +5

We present Decentralized Distributed Proximal Policy Optimization (DD-PPO), a method for distributed reinforcement learning in resource-intensive simulated environments. DD-PPO is…

cs.LG2019

Improving Generative Visual Dialog by Answering Diverse Questions

Vishvak Murahari, Prithvijit Chattopadhyay, Dhruv Batra +2

Prior work on training generative Visual Dialog models with reinforcement learning(Das et al.) has explored a Qbot-Abot image-guessing game and shown that this 'self-talk' approach…

cs.CV2019

ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks

Jiasen Lu, Dhruv Batra, Devi Parikh +1

We present ViLBERT (short for Vision-and-Language BERT), a model for learning task-agnostic joint representations of image content and natural language. We extend the popular BERT…

cs.LG2019

IR-VIC: Unsupervised Discovery of Sub-goals for Transfer in RL

Nirbhay Modhe, Prithvijit Chattopadhyay, Mohit Sharma +4

We propose a novel framework to identify sub-goals useful for exploration in sequential decision making tasks under partial observability. We utilize the variational intrinsic cont…