Papers
16
Total Citations
283
H-Index
9
About
Sajid Javed is a computer vision researcher whose work spans visual object tracking, underwater image enhancement, robotic perception, and autonomous systems. He is perhaps best known for his comprehensive survey on visual object tracking, "Handcrafted and Deep Trackers," which has accumulated over 118 citations and stands as a key reference for researchers navigating the rapidly evolving landscape of tracking algorithms — from classical handcrafted approaches to modern deep learning methods. Building on this foundation, Javed has contributed novel tracking frameworks such as the Hierarchical Spatiotemporal Graph Regularized Discriminative Correlation Filter, advancing the accuracy and robustness of real-time object tracking in complex visual environments. Beyond tracking, Javed has made meaningful strides in underwater vision, developing transformer-based and lightweight super-resolution architectures — including SwinWave-SR and a window-based GAN — that address the unique degradation challenges of underwater imagery. His work also extends to UAV-based industrial inspection, robotic grasping in cluttered scenes, and person-following robots in challenging uniform-appearance environments. With a cumulative citation count exceeding 260 across diverse high-impact topics, Javed's research reflects a broad yet cohesive commitment to advancing intelligent visual perception systems for real-world autonomous applications.
Research Focus
Key Achievements
Top Papers
- 1Handcrafted and Deep Trackers118 citations · 2019
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- 3SwinWave-SR: Multi-scale lightweight underwater image super-resolution29 citations · 2023
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- 10Real-Time Face Recognition System8 citations · 2022