331 citations · 761 across the 49 of their papers we have counts for
43 papers · 1 filter
What's Old is New Again: Classical Dimensionality Reduction for Efficient Saliency-Guided Biometric Attack Detection
Samuel Webster, Walter Scheirer
Saliency-guided training is a paradigm in visual recognition that encourages models to focus on the most relevant image regions during learning. While its application in biometric…
Pixel-Grounded Prototypical Part Networks
Zachariah Carmichael, Suhas Lohit, Anoop Cherian +2
Prototypical part neural networks (ProtoPartNNs), namely PROTOPNET and its derivatives, are an intrinsically interpretable approach to machine learning. Their prototype learning sc…
On the Effectiveness of Image Manipulation Detection in the Age of Social Media
Rosaura G. VidalMata, Priscila Saboia, Daniel Moreira +3
Image manipulation detection algorithms designed to identify local anomalies often rely on the manipulated regions being ``sufficiently'' different from the rest of the non-tampere…
Using Human Perception to Regularize Transfer Learning
Justin Dulay, Walter J. Scheirer
Recent trends in the machine learning community show that models with fidelity toward human perceptual measurements perform strongly on vision tasks. Likewise, human behavioral mea…
Psychophysical-Score: A Behavioral Measure for Assessing the Biological Plausibility of Visual Recognition Models
Brandon RichardWebster, Justin Dulay, Anthony DiFalco +2
For the last decade, convolutional neural networks (CNNs) have vastly superseded their predecessors in nearly all vision tasks in artificial intelligence, including object recognit…
Measuring Human Perception to Improve Open Set Recognition
Jin Huang, Derek Prijatelj, Justin Dulay +1
The human ability to recognize when an object belongs or does not belong to a particular vision task outperforms all open set recognition algorithms. Human perception as measured b…
Analyzing the Impact of Shape & Context on the Face Recognition Performance of Deep Networks
Sandipan Banerjee, Walter Scheirer, Kevin Bowyer +1
In this article, we analyze how changing the underlying 3D shape of the base identity in face images can distort their overall appearance, especially from the perspective of deep f…
Guiding Machine Perception with Psychophysics
Justin Dulay, Sonia Poltoratski, Till S. Hartmann +2
{G}{ustav} Fechner's 1860 delineation of psychophysics, the measurement of sensation in relation to its stimulus, is widely considered to be the advent of modern psychological scie…
Motif Mining: Finding and Summarizing Remixed Image Content
William Theisen, Daniel Gonzalez Cedre, Zachariah Carmichael +3
On the internet, images are no longer static; they have become dynamic content. Thanks to the availability of smartphones with cameras and easy-to-use editing software, images can…
Forensic Analysis of Synthetically Generated Western Blot Images
Sara Mandelli, Davide Cozzolino, Edoardo D. Cannas +8
The widespread diffusion of synthetically generated content is a serious threat that needs urgent countermeasures. As a matter of fact, the generation of synthetic content is not r…
A Study of the Human Perception of Synthetic Faces
Bingyu Shen, Brandon RichardWebster, Alice O'Toole +2
Advances in face synthesis have raised alarms about the deceptive use of synthetic faces. Can synthetic identities be effectively used to fool human observers? In this paper, we in…
Handwriting Recognition with Novelty
Derek S. Prijatelj, Samuel Grieggs, Futoshi Yumoto +2
This paper introduces an agent-centric approach to handle novelty in the visual recognition domain of handwriting recognition (HWR). An ideal transcription agent would rival or sur…
A Bayesian Evaluation Framework for Subjectively Annotated Visual Recognition Tasks
Derek S. Prijatelj, Mel McCurrie, Walter J. Scheirer
An interesting development in automatic visual recognition has been the emergence of tasks where it is not possible to assign objective labels to images, yet still feasible to coll…
The Criminality From Face Illusion
Kevin W. Bowyer, Michael King, Walter Scheirer +1
The automatic analysis of face images can generate predictions about a person's gender, age, race, facial expression, body mass index, and various other indices and conditions. A f…
Learning Transformation-Aware Embeddings for Image Forensics
Aparna Bharati, Daniel Moreira, Patrick Flynn +3
A dramatic rise in the flow of manipulated image content on the Internet has led to an aggressive response from the media forensics research community. New efforts have incorporate…
Joint Visual-Temporal Embedding for Unsupervised Learning of Actions in Untrimmed Sequences
Rosaura G. VidalMata, Walter J. Scheirer, Anna Kukleva +2
Understanding the structure of complex activities in untrimmed videos is a challenging task in the area of action recognition. One problem here is that this task usually requires a…
Automatic Discovery of Political Meme Genres with Diverse Appearances
William Theisen, Joel Brogan, Pamela Bilo Thomas +4
Forms of human communication are not static -- we expect some evolution in the way information is conveyed over time because of advances in technology. One example of this phenomen…
UG Track 2: A Collective Benchmark Effort for Evaluating and Advancing Image Understanding in Poor Visibility Environments
Ye Yuan, Wenhan Yang, Wenqi Ren +3
The UG challenge in IEEE CVPR 2019 aims to evoke a comprehensive discussion and exploration about how low-level vision techniques can benefit the high-level automatic visual…
Measuring Human Perception to Improve Handwritten Document Transcription
Samuel Grieggs, Bingyu Shen, Greta Rauch +5
The subtleties of human perception, as measured by vision scientists through the use of psychophysics, are important clues to the internal workings of visual recognition. For insta…
Dynamic Spatial Verification for Large-Scale Object-Level Image Retrieval
Joel Brogan, Aparna Bharati, Daniel Moreira +4
Images from social media can reflect diverse viewpoints, heated arguments, and expressions of creativity, adding new complexity to retrieval tasks. Researchers working onContent-Ba…
Learning-Free Iris Segmentation Revisited: A First Step Toward Fast Volumetric Operation Over Video Samples
Jeffery Kinnison, Mateusz Trokielewicz, Camila Carballo +2
Subject matching performance in iris biometrics is contingent upon fast, high-quality iris segmentation. In many cases, iris biometrics acquisition equipment takes a number of imag…
Bridging the Gap Between Computational Photography and Visual Recognition
Rosaura G. VidalMata, Sreya Banerjee, Brandon RichardWebster +21
What is the current state-of-the-art for image restoration and enhancement applied to degraded images acquired under less than ideal circumstances? Can the application of such algo…
Face Hallucination Revisited: An Exploratory Study on Dataset Bias
Klemen Grm, Martin Pernuš, Leo Cluzel +3
Contemporary face hallucination (FH) models exhibit considerable ability to reconstruct high-resolution (HR) details from low-resolution (LR) face images. This ability is commonly…
Backdooring Convolutional Neural Networks via Targeted Weight Perturbations
Jacob Dumford, Walter Scheirer
We present a new type of backdoor attack that exploits a vulnerability of convolutional neural networks (CNNs) that has been previously unstudied. In particular, we examine the app…