37 citations · 158 across the 41 of their papers we have counts for
14 papers · 1 filter
GRCD: Grounded Region Change Detection for Multi-Finding Chest X-Ray Pairs
OFM Riaz Rahman Aranya, Peyman Najafirad, Kevin Desai
Radiologists routinely compare current and prior chest X-rays to track disease progression, producing follow-up reports that describe multiple findings, each localised to an anatom…
FLAVARS: A Multimodal Foundational Language and Vision Alignment Model for Remote Sensing
Isaac Corley, Simone Fobi Nsutezo, Anthony Ortiz +4
Remote sensing imagery is dense with objects and contextual visual information. There is a recent trend to combine paired satellite images and text captions for pretraining perform…
Estimating Earthquake Magnitude in Sentinel-1 Imagery via Ranking
Daniele Rege Cambrin, Isaac Corley, Paolo Garza +1
Earthquakes are commonly estimated using physical seismic stations, however, due to the installation requirements and costs of these stations, global coverage quickly becomes impra…
Image Safeguarding: Reasoning with Conditional Vision Language Model and Obfuscating Unsafe Content Counterfactually
Mazal Bethany, Brandon Wherry, Nishant Vishwamitra +1
Social media platforms are being increasingly used by malicious actors to share unsafe content, such as images depicting sexual activity, cyberbullying, and self-harm. Consequently…
Seeing the roads through the trees: A benchmark for modeling spatial dependencies with aerial imagery
Caleb Robinson, Isaac Corley, Anthony Ortiz +3
Fully understanding a complex high-resolution satellite or aerial imagery scene often requires spatial reasoning over a broad relevant context. The human object recognition system…
Revisiting pre-trained remote sensing model benchmarks: resizing and normalization matters
Isaac Corley, Caleb Robinson, Rahul Dodhia +2
Research in self-supervised learning (SSL) with natural images has progressed rapidly in recent years and is now increasingly being applied to and benchmarked with datasets contain…
Single-View Height Estimation with Conditional Diffusion Probabilistic Models
Isaac Corley, Peyman Najafirad
Digital Surface Models (DSM) offer a wealth of height information for understanding the Earth's surface as well as monitoring the existence or change in natural and man-made struct…
ZRG: A Dataset for Multimodal 3D Residential Rooftop Understanding
Isaac Corley, Jonathan Lwowski, Peyman Najafirad
A crucial part of any home is the roof over our heads to protect us from the elements. In this paper we present the Zeitview Rooftop Geometry (ZRG) dataset for residential rooftop…
Supervising Remote Sensing Change Detection Models with 3D Surface Semantics
Isaac Corley, Peyman Najafirad
Remote sensing change detection, identifying changes between scenes of the same location, is an active area of research with a broad range of applications. Recent advances in multi…
Generalized Zero-Shot Learning using Multimodal Variational Auto-Encoder with Semantic Concepts
Nihar Bendre, Kevin Desai, Peyman Najafirad
With the ever-increasing amount of data, the central challenge in multimodal learning involves limitations of labelled samples. For the task of classification, techniques such as m…
Show Why the Answer is Correct! Towards Explainable AI using Compositional Temporal Attention
Nihar Bendre, Kevin Desai, Peyman Najafirad
Visual Question Answering (VQA) models have achieved significant success in recent times. Despite the success of VQA models, they are mostly black-box models providing no reasoning…
Adaptive Clustering of Robust Semantic Representations for Adversarial Image Purification
Samuel Henrique Silva, Arun Das, Ian Scarff +1
Deep Learning models are highly susceptible to adversarial manipulations that can lead to catastrophic consequences. One of the most effective methods to defend against such distur…
Stuttering Speech Disfluency Prediction using Explainable Attribution Vectors of Facial Muscle Movements
Arun Das, Jeffrey Mock, Henry Chacon +3
Speech disorders such as stuttering disrupt the normal fluency of speech by involuntary repetitions, prolongations and blocking of sounds and syllables. In addition to these disrup…
Learning from Few Samples: A Survey
Nihar Bendre, Hugo Terashima Marín, Peyman Najafirad
Deep neural networks have been able to outperform humans in some cases like image recognition and image classification. However, with the emergence of various novel categories, the…