1 citations · 2 across the 4 of their papers we have counts for
4 papers
AdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object Counting
Muhammad Ibraheem Siddiqui, Muhammad Haris Khan
Zero-shot object counting (ZOC) aims to count instances of arbitrary object categories specified only through textual prompts. Recent training-free approaches leverage foundation m…
CountZES: Counting via Zero-Shot Exemplar Discovery and Selection
Muhammad Ibraheem Siddiqui, Muhammad Haris Khan
Zero-shot object counting (ZOC) aims to count instances of unseen categories using only a class name. Existing exemplar-based methods discover candidate exemplars through random im…
Towards PerSense++: Advancing Training-Free Personalized Instance Segmentation in Dense Images
Muhammad Ibraheem Siddiqui, Muhammad Umer Sheikh, Hassan Abid +2
Segmentation in dense visual scenes poses significant challenges due to occlusions, background clutter, and scale variations. To address this, we introduce PerSense, an end-to-end,…
PerSense: Training-Free Personalized Instance Segmentation in Dense Images
Muhammad Ibraheem Siddiqui, Muhammad Umer Sheikh, Hassan Abid +1
The emergence of foundational models has significantly advanced segmentation approaches. However, challenges still remain in dense scenarios, where occlusions, scale variations, an…