An MBZUAI team led by Ph.D. student Dmitry Demidov won the Best Student Paper Award at VISAPP 2023 for their work on fine-grained visual classification. Their paper, 'Salient Mask-Guided Vision Transformer for Fine-Grained Classification,' introduces SM-ViT, a technique using a salient mask to improve Vision Transformer accuracy. The model focuses on defining characteristics of objects, outperforming standard ViT architecture, even with fewer or lower-resolution images. Why it matters: This award recognizes MBZUAI's contribution to advancing computer vision, particularly in applications requiring nuanced object recognition, such as robotics and automated systems.
MBZUAI students won an award at the Asian Conference on Computer Vision (ACCV) for their ObjectCompose method. ObjectCompose generates object-to-background variations of images to validate neural network performance. It helps developers test AI systems by adding variability to validation datasets without distorting the main object. Why it matters: This research offers a new approach to improve the robustness and reliability of computer vision models, which is crucial for real-world applications in the region.
MBZUAI faculty, researchers, and students presented eight academic papers at the 25th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2022) in Singapore. Seven of the accepted papers feature a master’s or doctoral student as first author. The papers are the outcome of two MBZUAI faculty led labs – BioMedical Image Analysis (BioMedIA) lab and SPriNT-AI. Why it matters: This highlights MBZUAI's growing prominence in medical image analysis and AI, showcasing the university's commitment to producing high-quality research and fostering young talent in the field.
MBZUAI had 30 papers accepted at the International Conference on Computer Vision (ICCV) in Paris, out of 8,260 submissions. Visiting Professor Ivan Laptev served as one of the ICCV Program Chairs. Two papers from MBZUAI researchers focused on analyzing moving images, with one introducing Video-FocalNets for action analysis and the other exploring the transfer of knowledge from still image analysis to video. Why it matters: MBZUAI's strong presence at ICCV demonstrates its growing prominence in the global computer vision research landscape.
MBZUAI students Hanoona Bangalath and Muhammad Maaz, with perfect GPAs, had papers accepted at ECCV 2022 ("Class-agnostic Object Detection with Multi-modal Transformer") and NeurIPS 2022 ("Bridging the Gap between Object and Image-level Representation for Open-Vocabulary Detection"). Both will stay at MBZUAI for their PhDs, crediting the university's resources and faculty. Their supervisor, Salman Khan, praised their curiosity and hard work, highlighting their role in building the institution's reputation. Why it matters: The success of these students underscores MBZUAI's potential to foster high-quality AI research and attract top talent to the UAE.