research
∙
07/21/2023
HybridAugment++: Unified Frequency Spectra Perturbations for Model Robustness
Convolutional Neural Networks (CNN) are known to exhibit poor generaliza...
share
research
∙
06/13/2023
VISION Datasets: A Benchmark for Vision-based InduStrial InspectiON
Despite progress in vision-based inspection algorithms, real-world indus...
research
∙
04/24/2023
Meta-tuning Loss Functions and Data Augmentation for Few-shot Object Detection
Few-shot object detection, the problem of modelling novel object detecti...
research
∙
04/28/2022
Streaming Multiscale Deep Equilibrium Models
We present StreamDEQ, a method that infers frame-wise representations on...
research
∙
01/26/2022
How Robust are Discriminatively Trained Zero-Shot Learning Models?
Data shift robustness has been primarily investigated from a fully super...
research
∙
01/15/2022
Towards Zero-shot Sign Language Recognition
This paper tackles the problem of zero-shot sign language recognition (Z...
research
∙
01/09/2022
Semantics-driven Attentive Few-shot Learning over Clean and Noisy Samples
Over the last couple of years few-shot learning (FSL) has attracted grea...
research
∙
10/23/2021
MaskSplit: Self-supervised Meta-learning for Few-shot Semantic Segmentation
Just like other few-shot learning problems, few-shot segmentation aims t...
research
∙
08/13/2021
Detection and Captioning with Unseen Object Classes
Image caption generation is one of the most challenging problems at the ...
research
∙
05/23/2021
Weakly Supervised Instance Attention for Multisource Fine-Grained Object Recognition with an Application to Tree Species Classification
Multisource image analysis that leverages complementary spectral, spatia...
research
∙
09/16/2020
Red Carpet to Fight Club: Partially-supervised Domain Transfer for Face Recognition in Violent Videos
In many real-world problems, there is typically a large discrepancy betw...
research
∙
08/17/2020
A Deep Dive into Adversarial Robustness in Zero-Shot Learning
Machine learning (ML) systems have introduced significant advances in va...
research
∙
08/27/2019
Key Protected Classification for Collaborative Learning
Large-scale datasets play a fundamental role in training deep learning m...
research
∙
07/31/2019
Image Captioning with Unseen Objects
Image caption generation is a long standing and challenging problem at t...
research
∙
07/24/2019
Zero-Shot Sign Language Recognition: Can Textual Data Uncover Sign Languages?
We introduce the problem of zero-shot sign language recognition (ZSSLR),...
research
∙
05/16/2019
Learning Visually Consistent Label Embeddings for Zero-Shot Learning
In this work, we propose a zero-shot learning method to effectively mode...
research
∙
03/19/2019
Cross-task weakly supervised learning from instructional videos
In this paper we investigate learning visual models for the steps of ord...
research
∙
01/18/2019
Multisource Region Attention Network for Fine-Grained Object Recognition in Remote Sensing Imagery
Fine-grained object recognition concerns the identification of the type ...
research
∙
05/19/2018
Wildest Faces: Face Detection and Recognition in Violent Settings
With the introduction of large-scale datasets and deep learning models c...
research
∙
05/16/2018
Zero-Shot Object Detection by Hybrid Region Embedding
Object detection is considered as one of the most challenging problems i...
research
∙
12/09/2017
Fine-Grained Object Recognition and Zero-Shot Learning in Remote Sensing Imagery
Fine-grained object recognition that aims to identify the type of an obj...
research
∙
05/04/2017
Attributes2Classname: A discriminative model for attribute-based unsupervised zero-shot learning
We propose a novel approach for unsupervised zero-shot learning (ZSL) of...
research
∙
10/03/2015
Approximate Fisher Kernels of non-iid Image Models for Image Categorization
The bag-of-words (BoW) model treats images as sets of local descriptors ...
research
∙
03/03/2015