Spatially-Aware Class-Agnostic Object Counting
Generalised object counting aims to estimate the number of instances of an arbitrary object category from a single image, but many recent methods can struggle on structurally complex objects due to limited spatial modelling. We present \textit{UpCount}, a class-agnostic counter designed to better preserve spatial structure. UpCount strengthens the visual representation by extracting multi-layer features from a ViT-B/16 encoder and reassembling them into a refined multi-scale pyramid that is spatially refined using Dense Prediction Transformers and FeatUp, yielding features with improved structural and spatial sensitivity; a proposal--verification counting head then identifies repeated pat...
| Authors | Robert Wijaya, Md. Tanvir Hossain, Amanda Kau et al. |
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| Primary category | cs.CV |
| Published | 18 July 2026 |
| Last updated at source | 26 July 2026 |
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