Search Results for author: Amir Rosenfeld

Found 13 papers, 2 papers with code

A Constructive Prediction of the Generalization Error Across Scales

no code implementations ICLR 2020 Jonathan S. Rosenfeld, Amir Rosenfeld, Yonatan Belinkov, Nir Shavit

In this work, we present a functional form which approximates well the generalization error in practice.

High-Level Perceptual Similarity is Enabled by Learning Diverse Tasks

no code implementations26 Mar 2019 Amir Rosenfeld, Richard Zemel, John K. Tsotsos

Predicting human perceptual similarity is a challenging subject of ongoing research.

The Elephant in the Room

1 code implementation9 Aug 2018 Amir Rosenfeld, Richard Zemel, John K. Tsotsos

We showcase a family of common failures of state-of-the art object detectors.

Object Detection

Totally Looks Like - How Humans Compare, Compared to Machines

no code implementations5 Mar 2018 Amir Rosenfeld, Markus D. Solbach, John K. Tsotsos

Perceptual judgment of image similarity by humans relies on rich internal representations ranging from low-level features to high-level concepts, scene properties and even cultural associations.

Bridging Cognitive Programs and Machine Learning

no code implementations16 Feb 2018 Amir Rosenfeld, John K. Tsotsos

While great advances are made in pattern recognition and machine learning, the successes of such fields remain restricted to narrow applications and seem to break down when training data is scarce, a shift in domain occurs, or when intelligent reasoning is required for rapid adaptation to new environments.


Challenging Images For Minds and Machines

no code implementations13 Feb 2018 Amir Rosenfeld, John K. Tsotsos

There is no denying the tremendous leap in the performance of machine learning methods in the past half-decade.

Intriguing Properties of Randomly Weighted Networks: Generalizing While Learning Next to Nothing

no code implementations2 Feb 2018 Amir Rosenfeld, John K. Tsotsos

The implications of this intriguing property of deep neural networks are discussed and we suggest ways to harness it to create more robust representations.

Priming Neural Networks

1 code implementation16 Nov 2017 Amir Rosenfeld, Mahdi Biparva, John K. Tsotsos

This process has been shown to be an effect of top-down signaling in the visual system triggered by the said cue.

Object Detection

Incremental Learning Through Deep Adaptation

no code implementations ICLR 2018 Amir Rosenfeld, John K. Tsotsos

Given an existing trained neural network, it is often desirable to learn new capabilities without hindering performance of those already learned.

Continual Learning Image Classification +2

Visual Concept Recognition and Localization via Iterative Introspection

no code implementations14 Mar 2016 Amir Rosenfeld, Shimon Ullman

Convolutional neural networks have been shown to develop internal representations, which correspond closely to semantically meaningful objects and parts, although trained solely on class labels.

General Classification

Face-space Action Recognition by Face-Object Interactions

no code implementations17 Jan 2016 Amir Rosenfeld, Shimon Ullman

Action recognition in still images has seen major improvement in recent years due to advances in human pose estimation, object recognition and stronger feature representations.

Action Recognition In Still Images Object Recognition +1

Hand-Object Interaction and Precise Localization in Transitive Action Recognition

no code implementations12 Nov 2015 Amir Rosenfeld, Shimon Ullman

In this paper we demonstrate how recognition is improved by obtaining precise localization of the action-object and consequently extracting details of the object shape together with the actor-object interaction.

Action Recognition In Still Images Object Recognition +2

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