Debasmit Das | DeepAI

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∙ 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 ...

0 Jungsoo Lee, et al. ∙

∙ 04/02/2023

Progressive Random Convolutions for Single Domain Generalization

Single domain generalization aims to train a generalizable model with on...

2 Seokeon Choi, et al. ∙

∙ 03/02/2023

DejaVu: Conditional Regenerative Learning to Enhance Dense Prediction

We present DejaVu, a novel framework which leverages conditional image r...

0 Shubhankar Borse, et al. ∙

∙ 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...

0 Debasmit Das, et al. ∙

∙ 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...

0 Kambiz Azarian, et al. ∙

∙ 06/28/2022

Domain Agnostic Few-shot Learning for Speaker Verification

Deep learning models for verification systems often fail to generalize t...

10 Seunghan Yang, et al. ∙

∙ 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...

10 Shubhankar Borse, et al. ∙

∙ 11/24/2021

Distribution Estimation to Automate Transformation Policies for Self-Supervision

In recent visual self-supervision works, an imitated classification obje...

19 Seunghan Yang, et al. ∙

∙ 05/02/2021

Data-driven Weight Initialization with Sylvester Solvers

In this work, we propose a data-driven scheme to initialize the paramete...

0 Debasmit Das, et al. ∙

∙ 10/22/2020

Few-shot Image Recognition with Manifolds

In this paper, we extend the traditional few-shot learning (FSL) problem...

10 Debasmit Das, et al. ∙

∙ 02/20/2020

Multi-step Online Unsupervised Domain Adaptation

In this paper, we address the Online Unsupervised Domain Adaptation (OUD...

23 J. H. Moon, et al. ∙

∙ 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 ...

18 Debasmit Das, et al. ∙

∙ 03/27/2019

Zero-shot Image Recognition Using Relational Matching, Adaptation and Calibration

Zero-shot learning (ZSL) for image classification focuses on recognizing...

0 Debasmit Das, et al. ∙

∙ 05/22/2018

Unsupervised Domain Adaptation using Regularized Hyper-graph Matching

Domain adaptation (DA) addresses the real-world image classification pro...

0 Debasmit Das, et al. ∙

∙ 05/01/2018

Sample-to-Sample Correspondence for Unsupervised Domain Adaptation

The assumption that training and testing samples are generated from the ...

0 Debasmit Das, et al. ∙

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