Moushumi Medhi

PhD Candidate @ IIT Kharagpur


Hello! I am a Ph.D student at Indian Institute of Technology (IIT) Kharagpur, advised by Prof. Rajiv Ranjan Sahay. Previously, I worked as a Research Consultant in the Department of Electrical Engineering at IIT Kharagpur with Professor Sahay, on an industry-sponsored project funded by and delivered to Altair Engineering India Pvt. Ltd., Bangalore. Before that, I received my M.Tech. in Electronics and Communication Engineering from Tezpur Central University, where I worked on a government-funded project under the Council of Scientific and Industrial Research (CSIR), carried out at the CSIR–Central Electronics Engineering Research Institute (CSIR-CEERI), Pilani. As a master's dissertation intern at CSIR–CEERI, I was supervised by Dr. Ing. Jagdish Lal Raheja. I hold a B.Tech. in Electronics and Telecommunication Engineering from Assam Engineering College.

My research interests broadly lie in Machine Learning and Computer Vision, with a focus on generative AI and 3D vision. During my PhD, my thesis work has centered on developing and optimizing lightweight generative models to improve speed and efficiency of ill-posed 2D-3D vision problems (e.g., depth restoration, depth estimation) under limited data and constrained compute resources. Beyond my thesis, my research has explored the integration of physical image formation models with learning-based approaches. This includes work on depth from defocus, geometry-aware scene reconstruction from light field images, and generative representations for realistic view synthesis and restoration. I have also engaged with emerging topics at the intersection of vision and language, augmented reality, diffusion-based generative modeling, and classification and pattern recognition-based problems.

Publications

(*equal contribution, ✉ corresponding author)



Dark Channel-Assisted Depth-from-Defocus from a Single Image

Moushumi Medhi, Rajiv Ranjan Sahay

Preprint 2025



Adversarial Learning for Unguided Single Depth Map Completion of Indoor Scenes

Moushumi Medhi, Rajiv Ranjan Sahay

MVA 2025



Deep Generative Adversarial Network for Occlusion Removal from a Single Image

Sankaraganesh Jonna, Moushumi Medhi, Rajiv Ranjan Sahay

Preprint 2024



Distill-DBDGAN: Knowledge Distillation and Adversarial Learning Framework for Defocus Blur Detection

Sankaraganesh Jonna*, Moushumi Medhi*, Rajiv Ranjan Sahay

ACM TOMM 2023



Deep Two-Stage LiDAR Depth Completion

Moushumi Medhi, Rajiv Ranjan Sahay

Conference on Computer Vision and Image Processing (CVIP 2025), Best paper award



A Non-local Low-rank and Sparsity based Framework for Depth Map Inpainting

Sankaraganesh Jonna, Moushumi Medhi

ICCE 2020



Real-time Video Surveillance Based Structural Health Monitoring of Civil Structures Using Artificial Neural Network

Moushumi Medhi, Aradhana Dandautiya, Jagdish Lal Raheja

J. Nondestruct. Eval. 2019



A Text Recognition Augmented Deep Learning Approach for Logo Identification

Moushumi Medhi, Subham Sinha, Rajiv Ranjan Sahay

ICVGIP 2016