activity
20242026
collaborators

36 papers

cs.CV2026

Ground3D-LMM: Fine-Grained 3D Point Grounding and Spatial Reasoning with LMM

Amol Harsh, Zongyan Han, Jean Lahoud +5

Natural-language queries about 3D environments become actionable when responses are verifiable and metric. Verifiability requires explicit grounding to the referred 3D region, whil…

cs.CV2026

A Benchmark for Omni-Modal Reasoning in Long Videos

Mohammed Irfan Kurpath, Jaseel Muhammad Kaithakkodan, Jinxing Zhou +12

Long-form omni-modal video understanding requires integrating vision, speech, and ambient audio with coherent long-context reasoning. Existing video benchmarks often trade off temp…

cs.CV2026

EvoLMM: Self-Evolving Large Multimodal Models with Continuous Rewards

Omkar Thawakar, Shravan Venkatraman, Ritesh Thawkar +5

Recent advances in large multimodal models (LMMs) have enabled impressive reasoning and perception abilities, yet most existing training pipelines still depend on human-curated dat…

cs.CV2026

MAviS: A Multimodal Conversational Assistant For Avian Species

Yevheniia Kryklyvets, Mohammed Irfan Kurpath, Sahal Shaji Mullappilly +5

Fine-grained understanding and species-specific multimodal question answering are vital for advancing biodiversity conservation and ecological monitoring. However, existing multimo…

cs.CV2026

Agent-X: Evaluating Deep Multimodal Reasoning in Vision-Centric Agentic Tasks

Tajamul Ashraf, Amal Saqib, Hanan Ghani +11

Deep reasoning is fundamental for solving complex tasks, especially in vision-centric scenarios that demand sequential, multimodal understanding. However, existing benchmarks typic…

cs.CV2026

AI in Agriculture: A Survey of Deep Learning Techniques for Crops, Fisheries and Livestock

Umair Nawaz, Muhammad Zaigham Zaheer, Ufaq Khan +4

Crops, fisheries and livestock form the backbone of global food production, essential to feed the ever-growing global population. However, these sectors face considerable challenge…