9 citations · 13 across the 6 of their papers we have counts for
9 papers
X-DETR: A Versatile Architecture for Instance-wise Vision-Language Tasks
Zhaowei Cai, Gukyeong Kwon, Avinash Ravichandran +4
In this paper, we study the challenging instance-wise vision-language tasks, where the free-form language is required to align with the objects instead of the whole image. To addre…
Multi-Modal Learning Using Physicians Diagnostics for Optical Coherence Tomography Classification
Y. Logan, K. Kokilepersaud, G. Kwon +3
In this paper, we propose a framework that incorporates experts diagnostics and insights into the analysis of Optical Coherence Tomography (OCT) using multi-modal learning. To demo…
A Gating Model for Bias Calibration in Generalized Zero-shot Learning
Gukyeong Kwon, Ghassan AlRegib
Generalized zero-shot learning (GZSL) aims at training a model that can generalize to unseen class data by only using auxiliary information. One of the main challenges in GZSL is a…
Novelty Detection Through Model-Based Characterization of Neural Networks
Gukyeong Kwon, Mohit Prabhushankar, Dogancan Temel +1
In this paper, we propose a model-based characterization of neural networks to detect novel input types and conditions. Novelty detection is crucial to identify abnormal inputs tha…
Contrastive Explanations in Neural Networks
Mohit Prabhushankar, Gukyeong Kwon, Dogancan Temel +1
Visual explanations are logical arguments based on visual features that justify the predictions made by neural networks. Current modes of visual explanations answer questions of th…
Backpropagated Gradient Representations for Anomaly Detection
Gukyeong Kwon, Mohit Prabhushankar, Dogancan Temel +1
Learning representations that clearly distinguish between normal and abnormal data is key to the success of anomaly detection. Most of existing anomaly detection algorithms use act…