research
∙
08/14/2023
Towards Open-Set Test-Time Adaptation Utilizing the Wisdom of Crowds in Entropy Minimization
Test-time adaptation (TTA) methods, which generally rely on the model's ...
share
research
∙
04/02/2023
Progressive Random Convolutions for Single Domain Generalization
Single domain generalization aims to train a generalizable model with on...
research
∙
03/02/2023
DejaVu: Conditional Regenerative Learning to Enhance Dense Prediction
We present DejaVu, a novel framework which leverages conditional image r...
research
∙
02/24/2023
TransAdapt: A Transformative Framework for Online Test Time Adaptive Semantic Segmentation
Test-time adaptive (TTA) semantic segmentation adapts a source pre-train...
research
∙
12/12/2022
Test-time Adaptation vs. Training-time Generalization: A Case Study in Human Instance Segmentation using Keypoints Estimation
We consider the problem of improving the human instance segmentation mas...
research
∙
06/28/2022
Domain Agnostic Few-shot Learning for Speaker Verification
Deep learning models for verification systems often fail to generalize t...
research
∙
04/11/2022
Panoptic, Instance and Semantic Relations: A Relational Context Encoder to Enhance Panoptic Segmentation
This paper presents a novel framework to integrate both semantic and ins...
research
∙
11/24/2021
Distribution Estimation to Automate Transformation Policies for Self-Supervision
In recent visual self-supervision works, an imitated classification obje...
research
∙
05/02/2021
Data-driven Weight Initialization with Sylvester Solvers
In this work, we propose a data-driven scheme to initialize the paramete...
research
∙
10/22/2020
Few-shot Image Recognition with Manifolds
In this paper, we extend the traditional few-shot learning (FSL) problem...
research
∙
02/20/2020
Multi-step Online Unsupervised Domain Adaptation
In this paper, we address the Online Unsupervised Domain Adaptation (OUD...
research
∙
12/10/2019
A Two-Stage Approach to Few-Shot Learning for Image Recognition
This paper proposes a multi-layer neural network structure for few-shot ...
research
∙
03/27/2019
Zero-shot Image Recognition Using Relational Matching, Adaptation and Calibration
Zero-shot learning (ZSL) for image classification focuses on recognizing...
research
∙
05/22/2018
Unsupervised Domain Adaptation using Regularized Hyper-graph Matching
Domain adaptation (DA) addresses the real-world image classification pro...
research
∙
05/01/2018