activity
20122019
most citedTowards Fairer Datasets: Filtering and Balancing the Distribution of the People Subtree in the ImageNet Hierarchy

230 citations · 1.3k across the 31 of their papers we have counts for

collaborators

13 papers

cs.RO201911 cited

Scaling Robot Supervision to Hundreds of Hours with RoboTurk: Robotic Manipulation Dataset through Human Reasoning and Dexterity

Ajay Mandlekar, Jonathan Booher, Max Spero +6

Large, richly annotated datasets have accelerated progress in fields such as computer vision and natural language processing, but replicating these successes in robotics has been c…

cs.CV201646 cited

CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning

Justin Johnson, Bharath Hariharan, Laurens van der Maaten +3

When building artificial intelligence systems that can reason and answer questions about visual data, we need diagnostic tests to analyze our progress and discover shortcomings. Ex…

cs.CV20168 cited

Recurrent Attention Models for Depth-Based Person Identification

Albert Haque, Alexandre Alahi, Li Fei-Fei

We present an attention-based model that reasons on human body shape and motion dynamics to identify individuals in the absence of RGB information, hence in the dark. Our approach…

cs.HC201636 cited

A Glimpse Far into the Future: Understanding Long-term Crowd Worker Quality

Kenji Hata, Ranjay Krishna, Li Fei-Fei +1

Microtask crowdsourcing is increasingly critical to the creation of extremely large datasets. As a result, crowd workers spend weeks or months repeating the exact same tasks, makin…

cs.CV2016163 cited

Target-driven Visual Navigation in Indoor Scenes using Deep Reinforcement Learning

Yuke Zhu, Roozbeh Mottaghi, Eric Kolve +4

Two less addressed issues of deep reinforcement learning are (1) lack of generalization capability to new target goals, and (2) data inefficiency i.e., the model requires several (…

cs.CV2016111 cited

Visual Relationship Detection with Language Priors

Cewu Lu, Ranjay Krishna, Michael Bernstein +1

Visual relationships capture a wide variety of interactions between pairs of objects in images (e.g. "man riding bicycle" and "man pushing bicycle"). Consequently, the set of possi…