3 citations · 11 across the 8 of their papers we have counts for
9 papers
UnPose: Uncertainty-Guided Diffusion Priors for Zero-Shot Pose Estimation
Zhaodong Jiang, Ashish Sinha, Tongtong Cao +3
Estimating the 6D pose of novel objects is a fundamental yet challenging problem in robotics, often relying on access to object CAD models. However, acquiring such models can be co…
Ethical Medical Image Synthesis
Weina Jin, Ashish Sinha, Kumar Abhishek +1
The task of ethical Medical Image Synthesis (MISyn) is to ensure that the MISyn techniques are researched and developed ethically throughout their entire lifecycle, which is essent…
: Representing Anatomical Trees by Denoising Diffusion of Implicit Neural Fields
Ashish Sinha, Ghassan Hamarneh
Anatomical trees play a central role in clinical diagnosis and treatment planning. However, accurately representing anatomical trees is challenging due to their varying and complex…
DermSynth3D: Synthesis of in-the-wild Annotated Dermatology Images
Ashish Sinha, Jeremy Kawahara, Arezou Pakzad +6
In recent years, deep learning (DL) has shown great potential in the field of dermatological image analysis. However, existing datasets in this domain have significant limitations,…
MEnsA: Mix-up Ensemble Average for Unsupervised Multi Target Domain Adaptation on 3D Point Clouds
Ashish Sinha, Jonghyun Choi
Unsupervised domain adaptation (UDA) addresses the problem of distribution shift between the unlabelled target domain and labelled source domain. While the single target domain ada…
Deep Learning based Dimple Segmentation for Quantitative Fractography
Ashish Sinha, K S Suresh
In this work, we try to address the challenging problem of dimple detection and segmentation in Titanium alloys using machine learning methods, especially neural networks. The imag…