Computer Vision Decoded
Computer Vision Decoded is a podcast that explores the rapidly evolving field of computer vision and its impact on everyday life. Host Jared Heinly, Chief Scientist at EveryPoint, breaks down complex topics and recent developments so listeners can understand what they mean for them. Each episode aims to make the latest computer vision news accessible without requiring listeners to read lengthy articles.
Episodes
The Evolution of Image Based 3D Reconstruction
In this episode of Computer Vision Decoded, we bring to you a live recording of Jared Heinly presentation on the evolution of image based 3D reconstruction. This recording was from a Computer Vision Decoded meetup in Pittsburgh with a visual component. If you would like to tune in with the visuals, we recommend watching the episode on our YouTube channel: https://youtu.be/Gwib5IcTKHIFollo
Understanding Gaussian Splatting w/ NVIDIA's Ruilong Li
In this episode of Computer Vision Decoded, our hosts Jonathan Stephens and Jared Heinly are joined by Ruilong Li, a researcher at NVIDIA and key contributor to both Nerfstudio and gsplat, to dive deep into 3D Gaussian Splatting. They explore how this relatively new technology works, from the fundamentals of gaussian representations to the optimization process that creates photorealistic
Camera Types for 3D Reconstruction Explained
In this episode of Computer Vision Decoded, hosts Jonathan Stephens and Jared Heinly explore the various types of cameras used in computer vision and 3D reconstruction. They discuss the strengths and weaknesses of smartphone cameras, DSLR and mirrorless cameras, action cameras, drones, and specialized cameras like 360, thermal, and event cameras. The conversation emphasizes the importance
Understanding 3D Reconstruction with COLMAP
In this episode, Jonathan Stephens and Jared Heinly delve into the intricacies of COLMAP, a powerful tool for 3D reconstruction from images. They discuss the workflow of COLMAP, including feature extraction, correspondence search, incremental reconstruction, and the importance of camera models. The conversation also covers advanced topics like geometric verification, bundle adjustment, an
Tips and Tricks for 3D Reconstruction in Different Environments
In this episode, we discuss practical tips and challenges in 3D reconstruction from images, focusing on various environments such as urban, indoor, and outdoor settings. We explore issues like repetitive structures, lighting conditions, and the impact of reflections and shadows on reconstruction quality. The conversation also touches on the importance of camera motion, lens distortion, an
Exploring Depth Maps in Computer Vision
In this episode of Computer Vision Decoded, Jonathan Stephens and Jared Heinly explore the concept of depth maps in computer vision. They discuss the basics of depth and depth maps, their applications in smartphones, and the various types of depth maps. The conversation delves into the role of depth maps in photogrammetry and 3D reconstruction, as well as future trends in depth sensing an
What's New in 2025 for Computer Vision?
After an 18 month hiatus, we are back! In this episode of Computer Vision Decoded, hosts Jonathan Stephens and Jared Heinly discuss the latest advancements in computer vision technology, personal updates, and insights from the industry. They explore topics such as real-time 3D reconstruction, computer vision research, SLAM, event cameras, and the impact of generative AI on robotics. The c
A Computer Vision Scientist Reacts to the iPhone 15 Announcement
In this episode of Computer Vision Decoded, we are going to dive into our in-house computer vision expert's reaction to the iPhone 15 and iPhone 15 Pro announcement.We dive into the camera upgrades, decode what a quad sensor means, and even talk about the importance of depth maps.Episode timeline:00:00 Intro02:59 iPhone 15 Overview05:15 iPhone 15 Main Camera07:20 Quad Pixel Sensor Explain
OpenMVG Decoded: Pierre Moulon's 10 Year Journey Building Open-Source Software
In this episode of Computer Vision Decoded, we are going to dive into Pierre Moulon's 10 years experience building OpenMVG. We also cover the impact of open-source software in the computer vision industry and everything involved in building your own project. There is a lot to learn here!Our episode guest, Pierre Moulon, is a computer vision research scientist and creator of OpenMVG - a l
Understanding Implicit Neural Representations with Itzik Ben-Shabat
In this episode of Computer Vision Decoded, we are going to dive into implicit neural representations.We are joined by Itzik Ben-Shabat, a Visiting Research Fellow at the Australian National Universit (ANU) and Technion – Israel Institute of Technology as well as the host of the Talking Paper Podcast.You will learn a core understanding of implicit neural representations, key concepts and
From 2D to 3D: 4 Ways to Make a 3D Reconstruction from Imagery
In this episode of Computer Vision Decoded, we are going to dive into 4 different ways to 3D reconstruct a scene with images. Our cohost Jared Heinly, a PhD in the computer science specializing in 3D reconstruction from images, will dive into the 4 distinct strategies and discuss the pros and cons of each.Links to content shared in this episode:Live SLAM to measure a stockpile with SR Mea
From Concept to Reality: The Journey of Building Scaniverse
Join our guest, Keith Ito, founder of Scaniverse as we discuss the challenges of creating a 3D capture app for iPhones. Keith goes into depth on balancing speed with quality of 3D output and how he designed an intuitive user experience for his users.In this episode, we discuss…01:00 - Keith's Ito's background at Google09:44 - What is the Scaniverse app11:43 - What inspired Keith to build
Will NeRFs Replace Photogrammetry?
In this episode of Computer Vision Decoded, we are going to dive into one of the hottest topics in the industry: Neural Radiance Fields (NeRFs)We are joined by Matt Tancik, a student pursuing a PhD in the computer science and electrical engineering department at UC Berkeley. He has also contributed research to the original NeRF project in 2020 along with several others since then.Last but
How to Capture Images for 3D Reconstruction
In this episode of Computer Vision Decoded, we are going to dive into image capture best practices for 3D reconstruction.At the end of this livestream, you will have learned the basics for capturing scenes and objects. We will also provide a downloadable visual guide for reference on your next 3D reconstruction project.Download the official guide here to follow along: https://tinyurl.com/
Is The iPhone 14 Camera Any Good?
In this episode of Computer Vision Decoded, we join Jared Heinly and Jonathan Stephens from EveryPoint for their live reaction to the iPhone 14 series announcement. They go in depth into what all the camera specs mean to the average person. We also explain basics of computational photography and how Apple is able to get great photos from a small camera sensor.00:00 Intro02:43 Apple Watch
3D Reconstruction in the Wild
In this episode of Computer Vision Decoded, we sit down with Jared Heinly, Chief Scientist at EveryPoint, to discuss 3D reconstruction in the wild. What does “in the wild” mean? This means 3D reconstructing objects and scenes in non-controlled environments where you may have limitations with lighting, access, reflective surfaces, etc.00:00 Intro01:30: What are Duplicate Scene Structures a
What is the CVPR Conference?
In this episode of Computer Vision Decoded we dive into Jared Heinly's recent trip to the CVPR Conference. We cover: what the conference about, who should attend, what are the emerging trends in computer vision, how machine learning is being used in 3D reconstruction, and what NeRFs are for.00:00 - Introduction00:36 - What is CVPR?02:49 - Who should attend CVPR?08:11 - What are emerging t
What Do the WWDC Announcements Mean for Computer Vision?
In this inaugural episode of Computer Vision Decoded we dive into the recent announcements at WWDC 2022 and find out what they mean for the computer vision community. We talk about what Apple is doing with their new RoomPlan API and how computer vision scientists can leverage it for better experiences. We also cover the enhancements to video and photo capture during an active ARKit Sessio
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