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cs.CV2026

Objects Before Words: Object-First Inductive Biases for Grounding Language in Child-View Video

Sathira Silva, Abrham Kahsay Gebreselasie, Muhammad Umer Sheikh +3

Learning grounded word meaning from natural experience requires resolving two ambiguities in infant-view recordings: when the named referent appears and where it is in a cluttered…

cs.CV2026

Agentic AI for Remote Sensing: Technical Challenges and Research Directions

Muhammad Akhtar Munir, Muhammad Umer Sheikh, Akashah Shabbir +5

Earth Observation (EO) is moving beyond static prediction toward multi-step analytical workflows that require coordinated reasoning over data, tools, and geospatial state. While fo…

cs.CV2025

Robust and Label-Efficient Deep Waste Detection

Hassan Abid, Khan Muhammad, Muhammad Haris Khan

Effective waste sorting is critical for sustainable recycling, yet AI research in this domain continues to lag behind commercial systems due to limited datasets and reliance on leg…

cs.CV2025

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,…

cs.CV20251 cited

ThinkGeo: Evaluating Tool-Augmented Agents for Remote Sensing Tasks

Akashah Shabbir, Muhammad Akhtar Munir, Akshay Dudhane +6

Recent progress in large language models (LLMs) has enabled tool-augmented agents capable of solving complex real-world tasks through step-by-step reasoning. However, existing eval…