349 citations · 447 across the 8 of their papers we have counts for
8 papers
Consensus and Subjectivity of Skin Tone Annotation for ML Fairness
Candice Schumann, Gbolahan O. Olanubi, Auriel Wright +3
Understanding different human attributes and how they affect model behavior may become a standard need for all model creation and usage, from traditional computer vision tasks to t…
A Step Toward More Inclusive People Annotations for Fairness
Candice Schumann, Susanna Ricco, Utsav Prabhu +2
The Open Images Dataset contains approximately 9 million images and is a widely accepted dataset for computer vision research. As is common practice for large datasets, the annotat…
Motion Prediction Under Multimodality with Conditional Stochastic Networks
Katerina Fragkiadaki, Jonathan Huang, Alex Alemi +3
Given a visual history, multiple future outcomes for a video scene are equally probable, in other words, the distribution of future outcomes has multiple modes. Multimodality is no…
AVA: A Video Dataset of Spatio-temporally Localized Atomic Visual Actions
Chunhui Gu, Chen Sun, David A. Ross +9
This paper introduces a video dataset of spatio-temporally localized Atomic Visual Actions (AVA). The AVA dataset densely annotates 80 atomic visual actions in 430 15-minute video…
SfM-Net: Learning of Structure and Motion from Video
Sudheendra Vijayanarasimhan, Susanna Ricco, Cordelia Schmid +2
We propose SfM-Net, a geometry-aware neural network for motion estimation in videos that decomposes frame-to-frame pixel motion in terms of scene and object depth, camera motion an…
Behavior Discovery and Alignment of Articulated Object Classes from Unstructured Video
Luca Del Pero, Susanna Ricco, Rahul Sukthankar +1
We propose an automatic system for organizing the content of a collection of unstructured videos of an articulated object class (e.g. tiger, horse). By exploiting the recurring mot…
Recovering Spatiotemporal Correspondence between Deformable Objects by Exploiting Consistent Foreground Motion in Video
Luca Del Pero, Susanna Ricco, Rahul Sukthankar +1
Given unstructured videos of deformable objects, we automatically recover spatiotemporal correspondences to map one object to another (such as animals in the wild). While tradition…
Articulated motion discovery using pairs of trajectories
Luca Del Pero, Susanna Ricco, Rahul Sukthankar +1
We propose an unsupervised approach for discovering characteristic motion patterns in videos of highly articulated objects performing natural, unscripted behaviors, such as tigers…