20 citations · 20 across the 7 of their papers we have counts for
7 papers
SwinIFS: Landmark Guided Swin Transformer For Identity Preserving Face Super Resolution
Habiba Kausar, Saeed Anwar, Omar Jamal Hammad +2
Face super-resolution aims to recover high-quality facial images from severely degraded low-resolution inputs, but remains challenging due to the loss of fine structural details an…
C3Net: Context-Contrast Network for Camouflaged Object Detection
Baber Jan, Aiman H. El-Maleh, Abdul Jabbar Siddiqui +2
Camouflaged object detection identifies objects that blend seamlessly with their surroundings through similar colors, textures, and patterns. This task challenges both traditional…
MSRNet: A Multi-Scale Recursive Network for Camouflaged Object Detection
Leena Alghamdi, Muhammad Usman, Hafeez Anwar +2
Camouflaged object detection is an emerging and challenging computer vision task that requires identifying and segmenting objects that blend seamlessly into their environments due…
TDiR: Transformer based Diffusion for Image Restoration Tasks
Abbas Anwar, Ibrahim Radwan, Ali Arshad Nasir +2
Images captured in challenging environments often experience various types of degradation, such as noise, color cast, blur, and light scattering. These issues significantly lower i…
Segmenting Visuals With Querying Words: Language Anchors For Semi-Supervised Image Segmentation
Numair Nadeem, Saeed Anwar, Muhammad Hamza Asad +1
Vision Language Models (VLMs) provide rich semantic priors but are underexplored in Semi supervised Semantic Segmentation. Recent attempts to integrate VLMs to inject high level se…
MaskAdapt: Unsupervised Geometry-Aware Domain Adaptation Using Multimodal Contextual Learning and RGB-Depth Masking
Numair Nadeem, Muhammad Hamza Asad, Saeed Anwar +1
Semantic segmentation of crops and weeds is crucial for site-specific farm management; however, most existing methods depend on labor intensive pixel-level annotations. A further c…
AllWeatherNet:Unified Image Enhancement for Autonomous Driving under Adverse Weather and Lowlight-conditions
Chenghao Qian, Mahdi Rezaei, Saeed Anwar +4
Adverse conditions like snow, rain, nighttime, and fog, pose challenges for autonomous driving perception systems. Existing methods have limited effectiveness in improving essentia…