most citedEvalAI: Towards Better Evaluation Systems for AI Agents

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cs.CV20225 cited

Instance-Specific Image Goal Navigation: Training Embodied Agents to Find Object Instances

Jacob Krantz, Stefan Lee, Jitendra Malik +2

We consider the problem of embodied visual navigation given an image-goal (ImageNav) where an agent is initialized in an unfamiliar environment and tasked with navigating to a loca…

cs.CV2019

Sim2Real Predictivity: Does Evaluation in Simulation Predict Real-World Performance?

Abhishek Kadian, Joanne Truong, Aaron Gokaslan +6

Does progress in simulation translate to progress on robots? If one method outperforms another in simulation, how likely is that trend to hold in reality on a robot? We examine thi…

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.CV201911 cited

Question-Conditioned Counterfactual Image Generation for VQA

Jingjing Pan, Yash Goyal, Stefan Lee

While Visual Question Answering (VQA) models continue to push the state-of-the-art forward, they largely remain black-boxes - failing to provide insight into how or why an answer i…

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

Sunny and Dark Outside?! Improving Answer Consistency in VQA through Entailed Question Generation

Arijit Ray, Karan Sikka, Ajay Divakaran +2

While models for Visual Question Answering (VQA) have steadily improved over the years, interacting with one quickly reveals that these models lack consistency. For instance, if a…