168 citations · 212 across the 12 of their papers we have counts for
4 papers · 1 filter
Three approaches to facilitate DNN generalization to objects in out-of-distribution orientations and illuminations
Akira Sakai, Taro Sunagawa, Spandan Madan +7
The training data distribution is often biased towards objects in certain orientations and illumination conditions. While humans have a remarkable capability of recognizing objects…
Emergent Neural Network Mechanisms for Generalization to Objects in Novel Orientations
Avi Cooper, Xavier Boix, Daniel Harari +4
The capability of Deep Neural Networks (DNNs) to recognize objects in orientations outside the distribution of the training data is not well understood. We present evidence that DN…
In-distribution adversarial attacks on object recognition models using gradient-free search
Spandan Madan, Tomotake Sasaki, Hanspeter Pfister +2
Neural networks are susceptible to small perturbations in the form of 2D rotations and shifts, image crops, and even changes in object colors. Past works attribute these errors to…
When Pigs Fly: Contextual Reasoning in Synthetic and Natural Scenes
Philipp Bomatter, Mengmi Zhang, Dimitar Karev +3
Context is of fundamental importance to both human and machine vision; e.g., an object in the air is more likely to be an airplane than a pig. The rich notion of context incorporat…