research
∙
01/20/2020
Accuracy vs. Complexity: A Trade-off in Visual Question Answering Models
Visual Question Answering (VQA) has emerged as a Visual Turing Test to v...
share
research
∙
12/09/2019
Deep CMST Framework for the Autonomous Recognition of Heavily Occluded and Cluttered Baggage Items from Multivendor Security Radiographs
Since the last two decades, luggage scanning has become one of the prime...
research
∙
08/09/2019
Question-Agnostic Attention for Visual Question Answering
Visual Question Answering (VQA) models employ attention mechanisms to di...
research
∙
06/09/2019
Unsupervised Primitive Discovery for Improved 3D Generative Modeling
3D shape generation is a challenging problem due to the high-dimensional...
research
∙
05/28/2019
Cross-Domain Transferability of Adversarial Perturbations
Adversarial examples reveal the blind spots of deep neural networks (DNN...
research
∙
01/07/2019
Image Super-Resolution as a Defense Against Adversarial Attacks
Convolutional Neural Networks have achieved significant success across m...
research
∙
11/30/2018
From Known to the Unknown: Transferring Knowledge to Answer Questions about Novel Visual and Semantic Concepts
Current Visual Question Answering (VQA) systems can answer intelligent q...
research
∙
11/22/2018
Distorting Neural Representations to Generate Highly Transferable Adversarial Examples
Deep neural networks (DNN) can be easily fooled by adding human impercep...
research
∙
04/27/2018
Adversarial Training of Variational Auto-encoders for High Fidelity Image Generation
Variational auto-encoders (VAEs) provide an attractive solution to image...
research
∙
03/09/2018
Indoor Scene Understanding in 2.5/3D: A Survey
With the availability of low-cost and compact 2.5/3D visual sensing devi...
research
∙
06/27/2017
A Unified approach for Conventional Zero-shot, Generalized Zero-shot and Few-shot Learning
Prevalent techniques in zero-shot learning do not generalize well to oth...
research
∙
06/07/2016
Learning deep structured network for weakly supervised change detection
Conventional change detection methods require a large number of images t...
research
∙
06/18/2015
A Spatial Layout and Scale Invariant Feature Representation for Indoor Scene Classification
Unlike standard object classification, where the image to be classified ...
research
∙
06/17/2015
