6 papers
Low Light Image Enhancement Challenge at NTIRE 2026
George Ciubotariu, Sharif S M A, Abdur Rehman +90
This paper presents a comprehensive review of the NTIRE 2026 Low Light Image Enhancement Challenge, highlighting the proposed solutions and final results. The objective of this cha…
TriFusion-SR: Joint Tri-Modal Medical Image Fusion and SR
Fayaz Ali Dharejo, Sharif S. M. A., Aiman Khalil +3
Multimodal medical image fusion facilitates comprehensive diagnosis by aggregating complementary structural and functional information, but its effectiveness is limited by resoluti…
CLIP-Guided Multi-Task Regression for Multi-View Plant Phenotyping
Simon Warmers, Muhammad Zawish, Fayaz Ali Dharejo +2
Modeling plant growth dynamics plays a central role in modern agricultural research. However, learning robust predictors from multi-view plant imagery remains challenging due to st…
Illuminating Darkness: Learning to Enhance Low-light Images In-the-Wild
S M A Sharif, Abdur Rehman, Zain Ul Abidin +3
Single-shot low-light image enhancement (SLLIE) remains challenging due to the limited availability of diverse, real-world paired datasets. To bridge this gap, we introduce the Low…
Degradation-Aware All-in-One Image Restoration via Latent Prior Encoding
S M A Sharif, Abdur Rehman, Fayaz Ali Dharejo +2
Real-world images often suffer from spatially diverse degradations such as haze, rain, snow, and low-light, significantly impacting visual quality and downstream vision tasks. Exis…
ContextFormer: Redefining Efficiency in Semantic Segmentation
Mian Muhammad Naeem Abid, Nancy Mehta, Zongwei Wu +1
Semantic segmentation assigns labels to pixels in images, a critical yet challenging task in computer vision. Convolutional methods, although capturing local dependencies well, str…