activity
20162023
most citedVisual Transformer for Task-aware Active Learning

5 citations · 10 across the 8 of their papers we have counts for

collaborators
Showing cs.CVShow all

16 papers · 1 filter

cs.CV2023

A Client-server Deep Federated Learning for Cross-domain Surgical Image Segmentation

Ronast Subedi, Rebati Raman Gaire, Sharib Ali +3

This paper presents a solution to the cross-domain adaptation problem for 2D surgical image segmentation, explicitly considering the privacy protection of distributed datasets belo…

cs.CV2022

Generalized Product-of-Experts for Learning Multimodal Representations in Noisy Environments

Abhinav Joshi, Naman Gupta, Jinang Shah +3

A real-world application or setting involves interaction between different modalities (e.g., video, speech, text). In order to process the multimodal information automatically and…

cs.CV20222 cited

Task-Aware Active Learning for Endoscopic Image Analysis

Shrawan Kumar Thapa, Pranav Poudel, Binod Bhattarai +1

Semantic segmentation of polyps and depth estimation are two important research problems in endoscopic image analysis. One of the main obstacles to conduct research on these resear…

cs.CV2021

Brand Label Albedo Extraction of eCommerce Products using Generative Adversarial Network

Suman Sapkota, Manish Juneja, Laurynas Keleras +2

In this paper we present our solution to extract albedo of branded labels for e-commerce products. To this end, we generate a large-scale photo-realistic synthetic data set for alb…

cs.CV20215 cited

Visual Transformer for Task-aware Active Learning

Razvan Caramalau, Binod Bhattarai, Tae-Kyun Kim

Pool-based sampling in active learning (AL) represents a key framework for an-notating informative data when dealing with deep learning models. In this paper, we present a novel pi…

cs.CV2021

Label Geometry Aware Discriminator for Conditional Generative Networks

Suman Sapkota, Bidur Khanal, Binod Bhattarai +2

Multi-domain image-to-image translation with conditional Generative Adversarial Networks (GANs) can generate highly photo realistic images with desired target classes, yet these sy…