4 citations · 5 across the 9 of their papers we have counts for
7 papers · 1 filter
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…
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…
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…
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…
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…
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…
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…