Mohit Lamba

Papers

Total Citations

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About

Mohit Lamba is a computer vision researcher whose work centers on low-light image restoration and computational efficiency in deep learning systems. His most recognized contribution, "Towards Fast and Light-Weight Restoration of Dark Images" (2020), addresses one of the field's enduring challenges: capturing and reconstructing high-quality images under extreme low-light and near-zero lux conditions. Building upon the foundational work of Chen et al., Lamba's research pushes the boundaries of existing approaches by prioritizing not only image quality but also the speed and computational footprint of restoration models — a critical consideration for real-world deployment on resource-constrained devices such as smartphones and embedded systems. This work has garnered approximately 25 citations, reflecting meaningful engagement from the research community working at the intersection of image processing and efficient neural network design. Lamba's contributions are particularly relevant for students and practitioners interested in making advanced computer vision techniques accessible beyond high-performance computing environments, demonstrating that restoration quality need not come at the cost of prohibitive computational demands. His research represents an important step toward practical, scalable solutions for nighttime and low-light imaging applications.