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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 2019 · cs.CVShow all

17 papers · 2 filters

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.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.CV2019

Chasing Ghosts: Instruction Following as Bayesian State Tracking

Peter Anderson, Ayush Shrivastava, Devi Parikh +2

A visually-grounded navigation instruction can be interpreted as a sequence of expected observations and actions an agent following the correct trajectory would encounter and perfo…

cs.CV2019

RUBi: Reducing Unimodal Biases in Visual Question Answering

Remi Cadene, Corentin Dancette, Hedi Ben-younes +2

Visual Question Answering (VQA) is the task of answering questions about an image. Some VQA models often exploit unimodal biases to provide the correct answer without using the ima…

cs.CV2019

SplitNet: Sim2Sim and Task2Task Transfer for Embodied Visual Navigation

Daniel Gordon, Abhishek Kadian, Devi Parikh +2

We propose SplitNet, a method for decoupling visual perception and policy learning. By incorporating auxiliary tasks and selective learning of portions of the model, we explicitly…