3 papers
cs.CV2026
Contrastive-SDXL: Annotation-Preserving Night-Time Augmentation for Pedestrian Detection
Franky George, Muhammad Khalid, Adil Khan
Night-time pedestrian detection remains challenging because labelled night-time data are limited and large illumination differences make daytime-only trained detectors unreliable.…
cs.LG2026
Concepts' Information Bottleneck Models
Karim Galliamov, Syed M Ahsan Kazmi, Adil Khan +1
Concept Bottleneck Models (CBMs) aim to deliver interpretable predictions by routing decisions through a human-understandable concept layer, yet they often suffer reduced accuracy…
cs.CV2025
LLM-guided Instance-level Image Manipulation with Diffusion U-Net Cross-Attention Maps
Andrey Palaev, Adil Khan, Syed M. Ahsan Kazmi
The advancement of text-to-image synthesis has introduced powerful generative models capable of creating realistic images from textual prompts. However, precise control over image…