Mohbat Tharani
Mohbat Tharani is a Research Assistant in Computer Vision & Graphics Lab (cvglab) at LUMS Syed Babar Ali School of Science and Engineering.
Similar Posts
ICIP2021 – Comprehensive Online Network Pruning via Learnable Scaling Factors
Muhammad Umair Haider and Murtaza Taj Abstract: One of the major challenges in deploying deep neural network architectures is their size which has an adverse effect on their inference time and memory requirements. Deep CNNs can either be pruned width-wise by removing filters or depth-wise by removing layers and blocks. Width wise pruning (filter pruning)…
Ali Hassan
Ali Hassan is a Research Assistant in Computer Vision Lab (cvlab ) at LUMS Syed Babar Ali School of Science and Engineering. Research Interest My main areas of interest are Computer Vision, Machine Learning and Robotics. I am primarily interested in Human Motion Analysis. I am currently working on “Human Body Pose Estimation from Monocular…
Amjad Ali Mughal
Amjad is a Graphics Engineer in Computer Vision & Graphics Lab (cvglab) at LUMS Syed Babar Ali School of Science and Engineering. His area of expertise are designing and modeling, virtual tours and Laser Scanning See Also: http://heritage360.pk
MS Thesis Defense: Muhammad Ahmed Bhimra
Spatio-Temporal Analysis of Landuse-Landcover Change Using Satellite Imagery Thursday 28 Feb, 2019 at 10:00 am in Smart Room 9-105 SBASSE. Abstract We propose an approach to recognize large scale, rapid spatio-temporal analysis of satellite remote sensing data. This technique can be used to measure longitudinal changes and yearly changes. Most of the existing methods either…
ICASSP2022 -Camera Calibration through Camera Projection Loss
Talha Hanif Butt, Murtaza Taj Abstract: Camera calibration is a necessity in various tasks including 3D reconstruction, hand-eye coordination for a robotic interaction, autonomous driving, etc. In this work we propose a novel method to predict extrinsic (baseline, pitch, and translation), intrinsic (focal length and principal point offset) parameters using an image pair. Unlike existing…