May 16, 2024, 3:13 p.m. | Subarna Tripathi

Towards Data Science - Medium towardsdatascience.com

We explore novel video representations methods that are equipped with long-form reasoning capability. This is part 1 focusing on video representation as graphs and how to learn light-weights graph neural networks for several downstream applications. Part II focuses on sparse video-text transformers. And Part III provides a sneak peek into our latest and greatest explorations.

Existing video architectures tend to hit computation or memory bottlenecks after processing only a few seconds of the video content. So, how do we enable …

applications capability cvpr cvpr-2024 editors pick explore form graph graph neural networks graphs how to learn iii learn light long-form-video multimodal learning networks neural networks novel part reasoning representation representation learning text transformers video

Doctoral Researcher (m/f/div) in Automated Processing of Bioimages

@ Leibniz Institute for Natural Product Research and Infection Biology (Leibniz-HKI) | Jena

Seeking Developers and Engineers for AI T-Shirt Generator Project

@ Chevon Hicks | Remote

Software Engineer for AI Training Data (School Specific)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Python)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Tier 2)

@ G2i Inc | Remote

Data Quality Intern

@ Syngenta Group | Toronto, Ontario, Canada