Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
A Diagram Is Worth A Dozen Images
Diagrams are common tools for representing complex concepts, relationships and events, often when it would be difficult to portray the same information with natural images. Understanding natural…
Are Elephants Bigger than Butterflies? Reasoning about Sizes of Objects
Human vision greatly benefits from the information about sizes of objects. The role of size in several visual reasoning tasks has been thoroughly explored in human perception and cognition. However,…
A Task-Oriented Approach for Cost-sensitive Recognition
With the recent progress in visual recognition, we have already started to see a surge of vision related real-world applications. These applications, unlike general scene understanding, are task…
Beyond Parity Constraints: Fourier Analysis of Hash Functions for Inference
Random projections have played an important role in scaling up machine learning and data mining algorithms. Recently they have also been applied to probabilistic inference to estimate properties of…
Creating Causal Embeddings for Question Answering with Minimal Supervision
A common model for question answering (QA) is that a good answer is one that is closely related to the question, where relatedness is often determined using generalpurpose lexical models such as…
Cross-Sentence Inference for Process Knowledge
For AI systems to reason about real world situations, they need to recognize which processes are at play and which entities play key roles in them. Our goal is to extract this kind of rolebased…
Deep3D: Fully Automatic 2D-to-3D Video Conversion with Deep Convolutional Neural Networks
We propose Deep3D, a fully automatic 2D-to-3D conversion algorithm that takes 2D images or video frames as input and outputs stereo 3D image pairs. The stereo images can be viewed with 3D glasses or…
Examples are not enough. Learn to criticize! Criticism for Interpretability
Example-based explanations are widely used in the effort to improve the interpretability of highly complex distributions. However, prototypes alone are rarely sufficient to represent the gist of the…
FigureSeer: Parsing Result-Figures in Research Papers
‘Which are the pedestrian detectors that yield a precision above 95% at 25% recall?’ Answering such a complex query involves identifying and analyzing the results reported in figures within several…
G-CNN: an Iterative Grid Based Object Detector
We introduce G-CNN, an object detection technique based on CNNs which works without proposal algorithms. G-CNN starts with a multi-scale grid of fixed bounding boxes. We train a regressor to move…