175 citations · 283 across the 12 of their papers we have counts for
6 papers · 1 filter
Action Genome: Actions as Composition of Spatio-temporal Scene Graphs
Jingwei Ji, Ranjay Krishna, Li Fei-Fei +1
Action recognition has typically treated actions and activities as monolithic events that occur in videos. However, there is evidence from Cognitive Science and Neuroscience that p…
Deep Bayesian Active Learning for Multiple Correct Outputs
Khaled Jedoui, Ranjay Krishna, Michael Bernstein +1
Typical active learning strategies are designed for tasks, such as classification, with the assumption that the output space is mutually exclusive. The assumption that these tasks…
Learning Predicates as Functions to Enable Few-shot Scene Graph Prediction
Apoorva Dornadula, Austin Narcomey, Ranjay Krishna +2
Scene graph prediction --- classifying the set of objects and predicates in a visual scene --- requires substantial training data. However, most predicates only occur a handful of…
Scene Graph Prediction with Limited Labels
Vincent S. Chen, Paroma Varma, Ranjay Krishna +3
Visual knowledge bases such as Visual Genome power numerous applications in computer vision, including visual question answering and captioning, but suffer from sparse, incomplete…
HYPE: A Benchmark for Human eYe Perceptual Evaluation of Generative Models
Sharon Zhou, Mitchell L. Gordon, Ranjay Krishna +3
Generative models often use human evaluations to measure the perceived quality of their outputs. Automated metrics are noisy indirect proxies, because they rely on heuristics or pr…
Information Maximizing Visual Question Generation
Ranjay Krishna, Michael Bernstein, Li Fei-Fei
Though image-to-sequence generation models have become overwhelmingly popular in human-computer communications, they suffer from strongly favoring safe generic questions ("What is…