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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…
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…
Crowdsourcing in Computer Vision
Adriana Kovashka, Olga Russakovsky, Li Fei-Fei +1
Computer vision systems require large amounts of manually annotated data to properly learn challenging visual concepts. Crowdsourcing platforms offer an inexpensive method to captu…
A Hierarchical Approach for Generating Descriptive Image Paragraphs
Jonathan Krause, Justin Johnson, Ranjay Krishna +1
Recent progress on image captioning has made it possible to generate novel sentences describing images in natural language, but compressing an image into a single sentence can desc…
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 (…
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…