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20172025
most citedHazeSpace2M: A Dataset for Haze Aware Single Image Dehazing

18 citations · 20 across the 4 of their papers we have counts for

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6 papers · 1 filter

cs.CV2025

From Satellite to Street: A Hybrid Framework Integrating Stable Diffusion and PanoGAN for Consistent Cross-View Synthesis

Khawlah Bajbaa, Abbas Anwar, Muhammad Saqib +3

Street view imagery has become an essential source for geospatial data collection and urban analytics, enabling the extraction of valuable insights that support informed decision-m…

cs.CV20251 cited

RDD4D: 4D Attention-Guided Road Damage Detection And Classification

Asma Alkalbani, Muhammad Saqib, Ahmed Salim Alrawahi +3

Road damage detection and assessment are crucial components of infrastructure maintenance. However, current methods often struggle with detecting multiple types of road damage in a…

cs.CV2024

Cefdet: Cognitive Effectiveness Network Based on Fuzzy Inference for Action Detection

Zhe Luo, Weina Fu, Shuai Liu +4

Action detection and understanding provide the foundation for the generation and interaction of multimedia content. However, existing methods mainly focus on constructing complex r…

cs.CV202418 cited

HazeSpace2M: A Dataset for Haze Aware Single Image Dehazing

Md Tanvir Islam, Nasir Rahim, Saeed Anwar +3

Reducing the atmospheric haze and enhancing image clarity is crucial for computer vision applications. The lack of real-life hazy ground truth images necessitates synthetic dataset…

cs.CV2021

VisDrone-CC2020: The Vision Meets Drone Crowd Counting Challenge Results

Dawei Du, Longyin Wen, Pengfei Zhu +52

Crowd counting on the drone platform is an interesting topic in computer vision, which brings new challenges such as small object inference, background clutter and wide viewpoint.…

cs.CV20171 cited

Towards a Dedicated Computer Vision Tool set for Crowd Simulation Models

Sultan Daud Khan, Muhammad Saqib, Michael Blumenstein

As the population of world is increasing, and even more concentrated in urban areas, ensuring public safety is becoming a taunting job for security personnel and crowd managers. Ma…