MBZUAI faculty member Dr. Hang Dai won first and second place in the Commands 4 Autonomous Vehicles (C4AV) Workshop Challenge at ECCV 2020. Dr. Dai participated in the competition as part of two teams, earning top spots for using AI in autonomous vehicles. The C4AV Workshop Challenge aims to develop models for joint understanding of vision and language in self-driving cars. Why it matters: This win demonstrates MBZUAI's commitment to advancing AI research and its applications in key areas like autonomous vehicles.
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.
Ivan Laptev from INRIA Paris presented a talk at MBZUAI on embodied multi-modal visual understanding, covering advancements in video understanding tasks like question answering and captioning. The talk highlighted recent work on vision-language navigation and manipulation. He argued that detailed understanding of the physical world through vision is still in early stages, discussing open research directions related to robotics and video generation. Why it matters: The discussion of robotics applications and future research directions in embodied AI could influence the direction of AI research and development in the UAE, particularly at MBZUAI.
KAUST's Visual Computing Center (VCC) is researching computer vision, image processing, and machine learning, with applications in self-driving cars, surveillance, and security. Professor Bernard Ghanem is working on teaching machines to understand visual data semantically, similar to how humans perceive the world. Self-driving cars use visual sensors to interpret traffic signals and detect obstacles, while computer vision also assists governments and corporations with security applications like facial recognition and detecting unattended luggage. Why it matters: Advancements in computer vision at KAUST can contribute to innovations in autonomous vehicles and enhance security measures in the region.
Dr. Xiaoming Liu from Michigan State University discussed computer vision techniques for 3D world understanding at a talk hosted by MBZUAI. The talk covered 3D reconstruction, detection, depth estimation, and velocity estimation, with applications in biometrics and autonomous driving. Dr. Liu also touched on anti-spoofing and fair face recognition research at MSU's Computer Vision Lab. Why it matters: Showcasing international experts and research directions helps to catalyze computer vision and 3D understanding research efforts within the UAE's AI ecosystem.
Pong C Yuen from Hong Kong Baptist University will present a talk on remote photoplethysmography (rPPG) detection. The talk will review the development of rPPG detection, share recent research, and discuss future directions. rPPG is a technology for non-contact computer vision and healthcare applications like heart rate estimation. Why it matters: Advancements in rPPG could enable new remote patient monitoring and diagnostic tools in the region, reducing the need for physical contact.
MBZUAI researchers presented a new approach to video analysis at ICCV in Paris, led by Syed Talal Wasim. The approach builds on still image processing techniques like focal modulation to analyze spatial and temporal information in video separately. It aims to improve temporal aggregation while avoiding the computational complexity of transformers. Why it matters: This research advances video understanding in computer vision by offering a more efficient method for temporal modeling, crucial for applications like activity recognition and video surveillance.