6 papers
Canonical Face Embeddings
David McNeely-White, Ben Sattelberg, Nathaniel Blanchard +1
We present evidence that many common convolutional neural networks (CNNs) trained for face verification learn functions that are nearly equivalent under rotation. More specifically…
Exploring the Interchangeability of CNN Embedding Spaces
David McNeely-White, Benjamin Sattelberg, Nathaniel Blanchard +1
CNN feature spaces can be linearly mapped and consequently are often interchangeable. This equivalence holds across variations in architectures, training datasets, and network task…
A Pose Proposal and Refinement Network for Better Object Pose Estimation
Ameni Trabelsi, Mohamed Chaabane, Nathaniel Blanchard +1
In this paper, we present a novel, end-to-end 6D object pose estimation method that operates on RGB inputs. Our approach is composed of 2 main components: the first component class…
Looking Ahead: Anticipating Pedestrians Crossing with Future Frames Prediction
Mohamed Chaabane, Ameni Trabelsi, Nathaniel Blanchard +1
In this paper, we present an end-to-end future-prediction model that focuses on pedestrian safety. Specifically, our model uses previous video frames, recorded from the perspective…
Getting the subtext without the text: Scalable multimodal sentiment classification from visual and acoustic modalities
Nathaniel Blanchard, Daniel Moreira, Aparna Bharati +1
In the last decade, video blogs (vlogs) have become an extremely popular method through which people express sentiment. The ubiquitousness of these videos has increased the importa…
A Neurobiological Evaluation Metric for Neural Network Model Search
Nathaniel Blanchard, Jeffery Kinnison, Brandon RichardWebster +2
Neuroscience theory posits that the brain's visual system coarsely identifies broad object categories via neural activation patterns, with similar objects producing similar neural…