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Vladimir Yugay

@vyuga3d.bsky.social
553 followers 55 following 39 posts

Doing research in 3D Computer Vision. Ph.D. student at the University of Amsterdam. Previously at TUM. vladimiryugay.github.io

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Vladimir Yugay @vyuga3d.bsky.social · 16/07/2026
It's been several weeks since I started my research internship at @nianticspatial.bsky.social in London. Excited to finally work with @ericbrachmann.bsky.social and the team!
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Vladimir Yugay @vyuga3d.bsky.social · 01/04/2026
⏩ GaME code release! github.com/VladimirYuga... Grab components for your 3D reconstruction pipeline: 🔹 Purely geometric out-of-view scene change detection 🔹 Outdated observations filtering 🔹 Evaluation videos of changing scenes Contributions welcome 🚀
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Vladimir Yugay @vyuga3d.bsky.social · 09/10/2025
I remember discussing this approach with you in Milano!
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Vladimir Yugay @vyuga3d.bsky.social · 07/10/2025
Thanks to the team, Kien Nguyen, Theo Gevers, @cgmsnoek.bsky.social, and @martin-r-oswald.bsky.social from the University of Amsterdam!
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Vladimir Yugay @vyuga3d.bsky.social · 07/10/2025
We experimented with different backbones, camera pose representations, scalability, and attention mechanisms. Our evaluation spans hundreds of full-length videos across various metrics, without aligning the predicted trajectory to the ground truth, to simulate a real-world application
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Vladimir Yugay @vyuga3d.bsky.social · 07/10/2025
VoT does not require calibration or post-optimization and operates in real-time, capable of processing thousands of frames. It is trained on a vast amount of real-world indoor data, but can work just fine in outdoor scenarios. It uses only camera poses as supervision, making it broadly accessible
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Vladimir Yugay @vyuga3d.bsky.social · 07/10/2025
📽️ Check out Visual Odometry Transformer! VoT is an end-to-end model for getting accurate metric camera poses from monocular videos. vladimiryugay.github.io/vot/
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Vladimir Yugay @vyuga3d.bsky.social · 24/06/2025
Will you release the slides?👀 They're superb
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Vladimir Yugay @vyuga3d.bsky.social · 10/06/2025
I will be presenting our previous work at CVPR Nashville. Drop by if you want to chat!
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Vladimir Yugay @vyuga3d.bsky.social · 10/06/2025
This work was conducted in collaboration wit Kersten Thies, @lucacarlone.bsky.social , Theo Gevers, @martin-r-oswald.bsky.social , and Lukas Schmid at the Computer Vision Group of the University of Amsterdam and the SPARKLab of @mit.edu
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Vladimir Yugay @vyuga3d.bsky.social · 10/06/2025
We evaluate our method on synthetic and real-world datasets that undergo significant changes, including the movement, removal, and addition of large pieces of furniture, cutlery, a coffee machine, and pictures on the walls
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Vladimir Yugay @vyuga3d.bsky.social · 10/06/2025
GaME detects scene changes and directly manipulates the 3D Gaussians to keep the map up to date. Additionally, our keyframe management system identifies and eliminates pixels that observe stale geometry, thereby minimizing the amount of discarded information
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Vladimir Yugay @vyuga3d.bsky.social · 10/06/2025
We found two main problems. First, the 3D Gaussian maps can not easily “optimize out” changes in the geometry on the fly. Second, frames observing the old state of the scene contaminate the optimization process, resulting in visual artifacts and inconsistencies
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Vladimir Yugay @vyuga3d.bsky.social · 10/06/2025
Imagine you want ot create a 3DGS map of your apartment. You reconstructed your kitchen and continued to the bedroom. While you are in the bedroom, someone has moved the chair and added a table in the kitchen without telling you. That’s what can happen with your reconstruction👇
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Vladimir Yugay @vyuga3d.bsky.social · 10/06/2025
Introducing “Gaussian Mapping of Evolving Scenes”! We present an RGBD mapping system with novel view synthesis capabilities that accurately reconstruct scenes that change over time vladimiryugay.github.io/game/
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Vladimir Yugay @vyuga3d.bsky.social · 11/05/2025
Resubmission mentality in marathons Munich 2023 -> 8 months prep -> COVID -> ❌ Amsterdam 2024 -> 6 months prep -> COVID -> ❌ Leiden 2025 -> 6 months prep -> lfg ✅
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Vladimir Yugay @vyuga3d.bsky.social · 19/03/2025
🔹@rerun.io visualisation script for easy debugging, analysis, and replaying of reconstruction results with minimal effort
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Vladimir Yugay @vyuga3d.bsky.social · 19/03/2025
🔹Fully Pythonic pose graph optimisation module. The core library live coding by the author is tremendously enlightening www.youtube.com/watch?v=yXWk...
youtube.com
Live coding Graph SLAM in Python (Part 1)
YouTube video by Jeff Irion
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Vladimir Yugay @vyuga3d.bsky.social · 19/03/2025
🔹Place recognition module based on a large vision model - no more annoying dependency chains for DBoVW or NetVLAD
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Vladimir Yugay @vyuga3d.bsky.social · 19/03/2025
🔹Simple yet efficient mechanism for correcting and merging multiple 3D Gaussian Splatting maps into a global map
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Vladimir Yugay @vyuga3d.bsky.social · 19/03/2025
⏩Code release for MAGiC-SLAM! github.com/VladimirYuga... We vibe-coded hard to make the code as simple as possible. Here are some features you can seamlessly integrate into your 3D reconstruction pipeline right away:
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Vladimir Yugay @vyuga3d.bsky.social · 19/03/2025
🔹DinoV2-based place recognition module - no more annoying dependency chains of DBoVW or NetVLAD
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Vladimir Yugay @vyuga3d.bsky.social · 19/03/2025
🔹A simple yet efficient mechanism for correcting and merging multiple 3D Gaussian Splatting sub-maps into a global map
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Vladimir Yugay @vyuga3d.bsky.social · 26/02/2025
Fantastic work! Can't wait to try it out!
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Vladimir Yugay @vyuga3d.bsky.social · 08/02/2025
It feels like a tighter bubble on bsky. It also seems that the more people are aligned, the less they engage
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Vladimir Yugay @vyuga3d.bsky.social · 18/12/2024
Ye ye. Or monst3r-project.github.io. One can use them as a prior for dynamic envs just like mast3r for static ones
monst3r-project.github.io
MonST3R: A Simple Approach for Estimating Geometry in the Presense of Motion
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Vladimir Yugay @vyuga3d.bsky.social · 18/12/2024
There's so much progress in there partially bc *3r and splats are inexpensive. GPU poor can iterate fast :)
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Vladimir Yugay @vyuga3d.bsky.social · 18/12/2024
Probably more methods for dynamic environments. Smth monst3r-like
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Vladimir Yugay @vyuga3d.bsky.social · 18/12/2024
Last year splats, this year *3r
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Vladimir Yugay @vyuga3d.bsky.social · 27/11/2024
This work was done with amazing collaborators Theo Gevers and @martin-r-oswald.bsky.social at the Computer Vision Group of the University of Amsterdam. 7/7
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Vladimir Yugay @vyuga3d.bsky.social · 27/11/2024
Finally, we extend evaluation to novel view synthesis on real-world datasets. By extracting sequences from the ego-centric Aria dataset to simulate multi-agent operations, we prepared a hold-out test with novel view trajectories, ensuring a comprehensive evaluation of our system's capabilities. 6/7
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Vladimir Yugay @vyuga3d.bsky.social · 27/11/2024
Our sub-maps inherently support local pose corrections provided by the loop closure module. Combined with an efficient caching scheme and a two-stage merging process, this allows for fast and precise global map reconstruction. 5/7
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Vladimir Yugay @vyuga3d.bsky.social · 27/11/2024
Inevitably, agents’ trajectories drift over the run. We tackle this by integrating a loop closure mechanism into our SLAM system. Additionally, we experiment with foundational vision model features for loop detection, with promising results in our benchmarks. 4/7
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Vladimir Yugay @vyuga3d.bsky.social · 27/11/2024
Scaling SLAM systems requires a careful balance between computational resources and speed. In our approach, agents manage their local maps independently communicating with a centralized server. We achieve significant performance gains by using 3DGS sub-maps with efficient tracking and caching 3/7
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Vladimir Yugay @vyuga3d.bsky.social · 27/11/2024
With the rise of AR/VR and an ever-growing number of gadgets, NVS-SLAM systems must scale up while achieving greater accuracy. A natural approach is to have multiple agents collaborate - proving that "the whole is greater than the sum of its parts." But what challenges still stand in the way? 2/7
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Vladimir Yugay @vyuga3d.bsky.social · 27/11/2024
Introducing “MAGiC-SLAM: Multi-Agent Gaussian Globally Consistent SLAM”! We do SLAM with novel view synthesis capabilities on multiple simultaneously operating agents! vladimiryugay.github.io/magic_slam/i... 1/7
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Vladimir Yugay @vyuga3d.bsky.social · 23/11/2024
Hey there! I'm working on 3d vision, can you please add me?
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Vladimir Yugay @vyuga3d.bsky.social · 23/11/2024
Hey there! I'm working on 3d vision, can you please add me?
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Vladimir Yugay @vyuga3d.bsky.social · 22/11/2024
Loop closure detection, worked a bit better than classical stuff
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