Object Localization

Follow this topic Ask about this topic

Momentum

10 papers in the last four weeks, up 100% on the four weeks before. 0.1% of all new papers.

Jul 13Week of Sep 28

Latest papers 62

All topics

ABACUS: Adapting Unified Foundation Model for Bridging Image Count Understanding and Generation
Date pendingAnindya Mondal, Sauradip Nag, Anjan DuttaRecent Vision-Language Models Counting
University of Surrey, United Kingdom & Simon Fraser University, Canada · University of Surrey, United Kingdom
Visual-SLAM for the detection of hidden tomatoes in greenhouses by Hierarchical Localization and GLOMAP for robotized harvesting
Date pendingFernando Cañadas-Aránega, José C. Moreno, José L. Blanco-Claraco +1Mediterranean Greenhouses Orb-Slam2
Department of Informatics, CIESOL, ceiA3, Universidad de Almería, Ctra. Sacramento s/n, Almería, 04120, Spain · Department of Engineering, CIESOL, ceiA3, Universidad de Almería, Ctra. Sacramento s/n, Almería, 04120, Spain

Date pending, cs.CVJ/K move · Enter open · S save

ABACUS: Adapting Unified Foundation Model for Bridging Image Count Understanding and Generation

Anindya Mondal, Sauradip Nag, Anjan Dutta

University of Surrey, United Kingdom & Simon Fraser University, Canada · University of Surrey, United Kingdom

Recent Vision-Language Models Counting Object Localization Task Arithmetic

Open paper AskPDF arXiv

We present ABACUS, a unified vision-language model that jointly addresses object counting, crowd counting, referring-expression counting, and count-faithful image generation within a single 3B-parameter model. ABACUS introduces three contributions: density-aware adaptive zooming paired with an objectness map from multi-head self-attention decomposition to spatially ground count predictions; a boundary-aware count policy trained via GRPO with nested local, boundary, and global rewards to eliminate over- and undercounting at crop boundaries; and a cycle-consistent GRPO strategy in which the frozen understanding branch scores generated candidates on count-deviation and aesthetic quality, closing the understanding-generation synergy gap without any external critic or annotation. ABACUS achieves state-of-the-art results across seven benchmarks spanning object counting (FSC-147, CARPK), crowd counting (ShanghaiTech A/B), referring-expression counting (REC-8K), count-faithful generation (CoCoCount, T2I-CompBench, GenEval), and count reasoning (CountQA), surpassing both task-specific specialists and larger generalist models. Project page is at https://mondalanindya.github.io/pages/ABACUS.

Momentum

Related topics

Latest papers 62

ABACUS: Adapting Unified Foundation Model for Bridging Image Count Understanding and Generation

Visual-SLAM for the detection of hidden tomatoes in greenhouses by Hierarchical Localization and GLOMAP for robotized harvesting