A Novel Compression Scheme Based on Hybrid Tucker-Vector Quantization Via Tensor Sketching for Dynamic Light Fields Acquired Through Coded Aperture Camera. - Joshitha Ravishankar; Mansi Sharma; Sally Khaidem (IC3D, 2021)

An Integrated Representation & Compression Scheme Based on Convolutional Autoencoders with 4D DCT Perceptual Encoding for High Dynamic Range Light Fields. - Sally Khaidem; Mansi Sharma (CoRR, 2022)

A Novel Light Field Coding Scheme Based on Deep Belief Network and Weighted Binary Images for Additive Layered Displays. - Sally Khaidem; Mansi Sharma (CoRR, 2022)

A Hybrid Tucker-VQ Tensor Sketch decomposition model for coding and streaming real world light fields using stack of differently focused images. - Joshitha Ravishankar; Mansi Sharma; Sally Khaidem (Pattern Recognit. Lett., 2022)

A Data-Driven Approach based on Dynamic Mode Decomposition for Efficient Encoding of Dynamic Light Fields. - Joshitha Ravishankar; Sally Khaidem; Mansi Sharma (CVPR Workshops, 2023)

A Novel Approach for Neuromorphic Vision Data Compression based on Deep Belief Network. - Sally Khaidem; Abhipraay Nevatia; Mansi Sharma (ICVGIP, 2023)

A Deep Belief Network Approach to Scalable Compression of Light Field Data for Auto-Stereoscopic Displays. - Sally Khaidem; Mansi Sharma (BMVC, 2024)

Lightweight and high-speed contextual intensity image reconstruction from event-based sensors with adaptive FastDynamicNet. - Sally Khaidem; Raghav Jangid; Mansi Sharma (J. Electronic Imaging, 2025)