52 citations · 100 across the 9 of their papers we have counts for
14 papers
Measuring Compositional Consistency for Video Question Answering
Mona Gandhi, Mustafa Omer Gul, Eva Prakash +3
Recent video question answering benchmarks indicate that state-of-the-art models struggle to answer compositional questions. However, it remains unclear which types of compositiona…
AGQA 2.0: An Updated Benchmark for Compositional Spatio-Temporal Reasoning
Madeleine Grunde-McLaughlin, Ranjay Krishna, Maneesh Agrawala
Prior benchmarks have analyzed models' answers to questions about videos in order to measure visual compositional reasoning. Action Genome Question Answering (AGQA) is one such ben…
Disentangled3D: Learning a 3D Generative Model with Disentangled Geometry and Appearance from Monocular Images
Ayush Tewari, Mallikarjun B R, Xingang Pan +3
Learning 3D generative models from a dataset of monocular images enables self-supervised 3D reasoning and controllable synthesis. State-of-the-art 3D generative models are GANs whi…
Differentiable 3D CAD Programs for Bidirectional Editing
Dan Cascaval, Mira Shalah, Phillip Quinn +3
Modern CAD tools represent 3D designs not only as geometry, but also as a program composed of geometric operations, each of which depends on a set of parameters. Program representa…
AGQA: A Benchmark for Compositional Spatio-Temporal Reasoning
Madeleine Grunde-McLaughlin, Ranjay Krishna, Maneesh Agrawala
Visual events are a composition of temporal actions involving actors spatially interacting with objects. When developing computer vision models that can reason about compositional…
Towards Understanding How Readers Integrate Charts and Captions: A Case Study with Line Charts
Dae Hyun Kim, Vidya Setlur, Maneesh Agrawala
Charts often contain visually prominent features that draw attention to aspects of the data and include text captions that emphasize aspects of the data. Through a crowdsourced stu…