Pinned
Rerun
1,713 posts
Rerun
@rerundotio
Joined December 2021
🧵1/ We’re very excited about SimpleRecon! It brings together state-of-the-art depth accuracy and competitive 3D scene reconstruction which makes it perfect for resource-constrained environments! We used @rerun to dig into its inner workings. #computervision #AI #ML
00:00- The upcoming Rerun 0.17 brings a huge increase in explicit control over your visualizations 🚀 In this video for example we dynamically change the visualizer that is applied on an entity from Mesh3D to Points3D and then edit the radius of the points. Because this mesh has vertex
00:00 - SimpleRecon in Rerun 0.16! SimpleRecon is a back-to-basics approach for 3D scene reconstruction from posed monocular images by @NianticLabs . It offers state-of-the-art depth accuracy and competitive 3D scene reconstruction, which makes it perfect for resource-constrained
00:00 - Sim-to-Rerun: Using Rerun to visualize CARLA simulator output through #ROS 2. This example visualizes simulated sensor data from the CARLA simulator for autonomous driving in Rerun. It’s built using Rerun’s new proof-of-concept C++ ROS2 bridge, which currently has support for a
00:00 - Visualize GLOMAP in Rerun! GLOMAP is a general purpose global structure-from-motion pipeline for image-based sparse reconstruction. As compared to COLMAP it provides a much more efficient and scalable reconstruction process, typically 1-2 orders of magnitude faster, with on-par
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🚀 Ready to take 3D reconstruction to the next level? Whether you're working on NeRF or 3DGS, our new method, GLOMAP, is here to impress! 🌟 It's faster and more accurate than COLMAP on several datasets. 🌐 Website: lpanaf.github.io/eccv24_glomap/ @mapo1, @LinfeiPan, J. Schönberger - Much of our communication around Rerun has been focused on computer vision and robotics use cases, but we have always thought of it as more general purpose than that. We want to give users the ability to easily visualize any multimodal data.
00:00 - Introducing Rerun 0.13! With this release Rerun is (to our knowledge) the first publicly available multimodal visualizer with timeline scrolling that supports live visualization of time series in the kHz range. This is made possible by a 20-30x performance increase of time
00:00 - Go2 in Rerun: visualizing @UnitreeRobotics Go2 quadruped using Rerun’s ROS 2 bridge PoC. This example visualizes the Go2 robot, its onboard sensor data, and how it sees the environment. It’s built using Rerun’s new proof-of-concept C++ ROS 2 bridge, which currently supports a
00:00 - Rerun 0.20 is out! 🗺📍🎥 It adds early support for geospatial data with the new GeoPoints and GeoLineStrings archetypes and a map view. It also adds H.264 video support to the native viewer together with many performance and stability improvements for video in Rerun.
00:00 - We're hiring a Senior Rust Backend Engineer! 🦀
- 💡 Visualization is to Physical AI data what print is to text. It needs to be available everywhere, in all layers of the stack, for data in all forms.
00:00 - Robots in Rerun, a glimpse of things to come! 🤖 🖼 This example shows @BostonDynamics Spot robot by combining its URDF and onboard sensor data. It is built using Rerun’s proof-of-concept C++ ROS1 bridge, which now works for limited use cases. For all you roboticists: Rerun is,
00:00 - Check out the Neural Graph Mapping for Dense SLAM with Efficient Loop Closure paper by @leonard_bruns, Jun Zhang, and Patric Jensfelt, visualized with Rerun. “Existing neural field-based SLAM methods typically employ a single monolithic field as their scene representation. This
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