We welcome you to CDS-KIAC talk on 05 December 2023 (Tuesday). The details are as below:
Speaker: Dr. Mrigank Rochan
Title: Advancing Visual Intelligence: Innovations Across Images, Videos, and Point Clouds
Date and time: 05 December 2023; 4 PM
Venue: CDS #102, Department of Computational and Data Sciences.
Abstract:
As the demand for advanced computer vision applications continues to grow, there is a pressing need to improve the understanding and interpretation of visual data. In this talk, I will present our efforts to push the boundaries of visual intelligence across multiple modalities, including images, videos, and point clouds, enabling more accurate and efficient analysis of diverse visual content. Firstly, I will introduce our method that can automatically localize the object in an image associated with a user-generated textual tag. Secondly, I will describe our work towards the automatic creation of a short visual summary or highlight of a long input video, allowing users to easily preview, search, and edit ever-growing video data. Thirdly, I will discuss our research on robust visual perception systems in autonomous driving, focusing specifically on LiDAR point cloud semantic segmentation. Finally, I will conclude with some interesting future directions.
Bio of Speaker:
Mrigank Rochan is an Assistant Professor in the Department of Computer Science at the University of Saskatchewan, Canada. He earned his PhD in Computer Science from the University of Manitoba in 2020. His research interests lie in computer vision and machine learning. He has published papers in top-tier computer vision and robotics conferences and journals, including CVPR, ICCV, ECCV, ICRA, and TPAMI. He received the 2020 Canadian Image Processing and Pattern Recognition Society (CIPPRS) John Barron Doctoral Dissertation Award for his doctoral dissertation on deep learning models for video abstraction, a prestigious national award given annually to the top PhD thesis defended in computer/robot vision at a Canadian university.
ALL ARE WELCOME
