What we’re about
Welcome to the Cupertino AI Technology Meetup Group! This is a community for tech enthusiasts, software developers, data scientists, and AI professionals interested in exploring the latest trends in artificial intelligence and machine learning. Whether you're a beginner or an expert in the field, join us for informative discussions, hands-on workshops, and networking opportunities with like-minded individuals. Let's stay ahead of the curve and share our knowledge and passion for AI technology in this rapidly evolving industry. Come be a part of our exciting AI-focused events and unleash the potential of intelligent machines together!
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See all- Network event47 attendees from 16 groups hostingECCV Redux: Day 1 - Nov 19Link visible for attendees
Missed the European Conference on Computer Vision (ECCV) last month? Have no fear, we have collected some of the best research from the show into a series of online events.
Fast and Photo-realistic Novel View Synthesis from Sparse Images
Novel view synthesis generates new perspectives of a scene from a set of 2D images, enabling 3D applications like VR/AR, robotics, and autonomous driving. Current state-of-the-art methods produce high-fidelity results but require a lot of images, while sparse-view approaches often suffer from artifacts or slow inference. In this talk, I will present my research work focused on developing fast and photorealistic novel view synthesis techniques capable of handling extremely sparse input views.
ECCV 2024 Paper: CoherentGS: Sparse Novel View Synthesis with Coherent 3D Gaussians
About the Speaker
Avinash Paliwal is a PhD Candidate in the Aggie Graphics Group at Texas A&M University. His research is focused on 3D Computer Vision and Computational Photography.
Robust Calibration of Large Vision-Language Adapters
We empirically demonstrate that popular CLIP adaptation approaches, such as Adapters, Prompt Learning, and Test-Time Adaptation, substantially degrade the calibration capabilities of the zero-shot baseline in the presence of distributional drift. We identify the increase in logit ranges as the underlying cause of miscalibration of CLIP adaptation methods, contrasting with previous work on calibrating fully-supervised models. Motivated by these observations, we present a simple and model-agnostic solution to mitigate miscalibration, by scaling the logit range of each sample to its zero-shot prediction logits
ECCV 2024 Paper: Robust Calibration of Large Vision-Language Adapters
About the Speaker
Balamurali Murugesan is currently pursuing his Ph.D. in developing reliable deep learning models. Earlier, he completed his master’s thesis on accelerating MRI reconstruction. He has published 25+ research articles in renowned venues.
Tree-of-Life Meets AI: Knowledge-guided Generative Models for Understanding Species Evolution
A central challenge in biology is understanding how organisms evolve and adapt to their environment, acquiring variations in observable traits across the tree of life. However, measuring these traits is often subjective and labor-intensive, making trait discovery a highly label-scarce problem. With the advent of large-scale biological image repositories and advances in generative modeling, there is now an opportunity to accelerate the discovery of evolutionary traits. This talk focuses on using generative models to visualize evolutionary changes directly from images without relying on trait labels.
ECCV 2024 Paper: Hierarchical Conditioning of Diffusion Models Using Tree-of-Life for Studying Species Evolution
About the Speaker
Mridul Khurana is a PhD student at Virginia Tech and a researcher with the NSF Imageomics Institute. His research focuses on AI4Science, leveraging multimodal generative modeling to drive discoveries across scientific domains.
Past events (2)
See all- Network event160 attendees from 16 groups hostingOct 24 - AI, Machine Learning and Computer Vision MeetupThis event has passed