activity
20242026
most citedMobiLlama: Towards Accurate and Lightweight Fully Transparent GPT

4 citations · 5 across the 9 of their papers we have counts for

collaborators

10 papers

cs.CV2026

Hard Vision, Easy Vision: What GPT-6 Astra Reveals Across Computer Vision

Hanoona Rasheed, Mohammed Irfan Kurpath, Bin Ren +3

Frontier general-purpose systems are rapidly expanding beyond visual understanding into capabilities traditionally handled by dedicated computer-vision models. As these capabilitie…

cs.CV2026

Locate Anything in Videos: Rethinking Efficient Generative Spatio-Temporal Video Grounding

Hanoona Rasheed, Haania Siddiqui, Ming-Hsuan Yang +2

Spatio-temporal video grounding (STVG) requires models to identify when a referred event occurs and localize the target entity throughout that interval. Existing multimodal large l…

cs.CV2025

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.CV2024

BiMediX2: Bio-Medical EXpert LMM for Diverse Medical Modalities

Sahal Shaji Mullappilly, Mohammed Irfan Kurpath, Sara Pieri +8

We introduce BiMediX2, a bilingual (Arabic-English) Bio-Medical EXpert Large Multimodal Model that supports text-based and image-based medical interactions. It enables multi-turn c…

cs.CV2024

CONDA: Condensed Deep Association Learning for Co-Salient Object Detection

Long Li, Nian Liu, Dingwen Zhang +6

Inter-image association modeling is crucial for co-salient object detection. Despite satisfactory performance, previous methods still have limitations on sufficient inter-image ass…

cs.CV2024

Learning Camouflaged Object Detection from Noisy Pseudo Label

Jin Zhang, Ruiheng Zhang, Yanjiao Shi +3

Existing Camouflaged Object Detection (COD) methods rely heavily on large-scale pixel-annotated training sets, which are both time-consuming and labor-intensive. Although weakly su…

cs.CV2024

Composed Video Retrieval via Enriched Context and Discriminative Embeddings

Omkar Thawakar, Muzammal Naseer, Rao Muhammad Anwer +4

Composed video retrieval (CoVR) is a challenging problem in computer vision which has recently highlighted the integration of modification text with visual queries for more sophist…

cs.CL2024★ 1 cited

PALO: A Polyglot Large Multimodal Model for 5B People

Muhammad Maaz, Hanoona Rasheed, Abdelrahman Shaker +6

In pursuit of more inclusive Vision-Language Models (VLMs), this study introduces a Large Multilingual Multimodal Model called PALO. PALO offers visual reasoning capabilities in 10…

cs.CV2024

Efficient Video Object Segmentation via Modulated Cross-Attention Memory

Abdelrahman Shaker, Syed Talal Wasim, Martin Danelljan +3

Recently, transformer-based approaches have shown promising results for semi-supervised video object segmentation. However, these approaches typically struggle on long videos due t…

cs.CL2024★ 4 cited

MobiLlama: Towards Accurate and Lightweight Fully Transparent GPT

Omkar Thawakar, Ashmal Vayani, Salman Khan +6

"Bigger the better" has been the predominant trend in recent Large Language Models (LLMs) development. However, LLMs do not suit well for scenarios that require on-device processin…