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What's New in 2025 for Computer Vision?

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Content provided by Jonathan Stephens. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Jonathan Stephens or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ro.player.fm/legal.

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 conversation highlights the importance of merging traditional techniques with modern machine learning approaches to solve real-world problems effectively.

Chapters

00:00 Intro & Personal Updates
04:36 Real-Time 3D Reconstruction on iPhones
09:40 Advancements in SfM
14:56 Event Cameras
17:39 Neural Networks in 3D Reconstruction
26:30 SLAM and Machine Learning Innovation
29:48 Applications of SLAM in Robotics
34:19 NVIDIA's Cosmos and Physical AI
40:18 Generative AI for Real-World Applications
43:50 The Future of Gaussian Splatting and 3D Reconstruction

This episode is brought to you by EveryPoint. Learn more about how EveryPoint is building an infinitely scalable data collection and processing platform for the next generation of spatial computing applications and services: https://www.everypoint.io

  continue reading

18 episoade

Artwork
iconDistribuie
 

Fetch error

Hmmm there seems to be a problem fetching this series right now. Last successful fetch was on July 14, 2025 21:32 (5M ago)

What now? This series will be checked again in the next day. If you believe it should be working, please verify the publisher's feed link below is valid and includes actual episode links. You can contact support to request the feed be immediately fetched.

Manage episode 466170984 series 3364101
Content provided by Jonathan Stephens. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Jonathan Stephens or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ro.player.fm/legal.

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 conversation highlights the importance of merging traditional techniques with modern machine learning approaches to solve real-world problems effectively.

Chapters

00:00 Intro & Personal Updates
04:36 Real-Time 3D Reconstruction on iPhones
09:40 Advancements in SfM
14:56 Event Cameras
17:39 Neural Networks in 3D Reconstruction
26:30 SLAM and Machine Learning Innovation
29:48 Applications of SLAM in Robotics
34:19 NVIDIA's Cosmos and Physical AI
40:18 Generative AI for Real-World Applications
43:50 The Future of Gaussian Splatting and 3D Reconstruction

This episode is brought to you by EveryPoint. Learn more about how EveryPoint is building an infinitely scalable data collection and processing platform for the next generation of spatial computing applications and services: https://www.everypoint.io

  continue reading

18 episoade

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