Nicholas Fry (@deepfry_n) header
Nicholas Fry (@deepfry_n) profile picture

PhD Candidate in Computing @imperialcollege

London, England
Joined May 2026
Photo by Nicholas Fry (@deepfry_n)Photo by Nicholas Fry (@deepfry_n)Photo by Nicholas Fry (@deepfry_n)Photo by Nicholas Fry (@deepfry_n)Photo by Nicholas Fry (@deepfry_n)
Nicholas Fry retweeted
Robotics opportunities at Machenta in London. (Hopefully they are getting furniture soon!)
On Tuesday, we announced @Machenta_ and Instant Robot Learning. Today, we’re looking for the next people to join us all in London! machenta.com/team Building Machenta with everyone here has been such an adventure. And above all, so much fun. Partly I think this is because we’ve been fortunate enough to find a group of people who are just extraordinarily passionate, about both the research and the startup experience. But partly, it’s the magic of instant learning. Every morning when you walk into the lab, you can dream up an entirely new task, teach the robot, and just see what happens next. Sometimes it works, sometimes it doesn’t. Either way, there’s something incredible about all huddling around together to watch. All these little moments become memories that stick. I’ll never forget the first time @vitalisvos19 showed me Instant Robot Learning on a bimanual robot, tidying up Christmas crackers last December. I’ll never forget the day an investor surprised us by turning up with a collection of their own objects to test the model on (it worked — phew!). And I’ll never forget the first day each new member of the team walked through the door and instantly became part of the gang. We’re moving quickly here, we work very hard, and we collaborate closely in a flat structure. Everyone brings their own expertise to a different part of Machenta, but there’s a real sense that we’re all building this together. We’re a very close team, working in person every day and sharing in all the little moments along the way. And we’re now going to go out and find the right people to join us for this next phase of the journey. We’ll give you real ownership and responsibility for your part of Machenta, and an opportunity to shape where we all take this together next. So if you’re excited to be part of this with us all, today we're hiring for five roles: • Member of Technical Staff — Robot Learning • Member of Technical Staff — Robot Control • Member of Technical Staff — Robot Simulation • Member of Technical Staff — 3D Machine Learning • Community Lead Come and say hi at machenta.com/team. See you there!
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Nicholas Fry retweeted
I wonder if something like this could be used for Star Wars fan films to track 3d lightsabers instead of using roto🤔
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Nicholas Fry retweeted
AgentSTAR is an agentic method for both reconstruction and tracking of articulated objects from monocular videos. We can now track through rapid motion, severe occlusion and thin objects! 

There’s no spoon but we can still track it 🥄
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I'll be presenting our work at #ECCV2026 in Malmö! 🇸🇪 Find me at the poster and demo sessions: Poster 📅 Thu 10 Sep, 10:30 📍 ExHall #272 Demo 📅 Sat 12 Sep, 8:00 📍 ExHall Also at NeuSLAM Workshop 🤖: Tue 8 Sep, 14:00, Malmö Arena Hotel
(1/3) I am happy to share our work on Triangle Splatting SLAM! We show the first RGB-D SLAM to use differentiable triangles as a 3D map representation. Our method enables online mesh-based deformations and collision checking via on-the-fly Delaunay triangulation.
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Nicholas Fry retweeted
(1/4) Two (co-)first-author papers at #ECCV2026 in Malmö 🇸🇪 📅 Thu 10 Sep, 10:30 📍 PixVOD → ExHall #78 📍 MLP-Splatting → ExHall #277
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Code is out ! nmjfry.github.io/triangle-sp… There is also an experimental branch using the rasteriser from kenji-tojo.github.io/publica… by @tojo_kenji - I haven't properly implemented densification, but it already looks promising.
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What if we had converged to using different hardware architectures for visual computing ? Check out how we render 3D Gaussians on a Coarse-Grained Reconfigurable Array (CGRA): nmjfry.github.io/ipu-3dgs/ Presented at EGSR 2026. Work with @alzugarayign, @MarkPupilli, @paulhjkelly and @AjdDavison
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Nicholas Fry retweeted
A brilliant talk from @deepfry_n from EGSR 2026 on his paper Rendering 3D Gaussians on a Graph Processor. We assign Gaussians to tiles, fully with on-chip SRAM, and pass them around efficiently as needed as the virtual camera moves viewpoint. Joint work with @alzugarayign, @MarkPupilli and Paul Kelly. Full talk here: youtu.be/OHfQk9J-CAg?si=1DyP…
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What if you could turn any number of photos (3, 8, 15, or even 60) into one clean 3D surface (pts & mesh) with Flow Matching? Check out our new work, Surflo: Consistent 3D Surface Flow Model with Global State. 🧵 1/n 🔗anttwo.github.io/surflo/
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Nicholas Fry retweeted
(1/5) Excited to introduce MLP-Splatting, a novel way to decompose a scene into object-/part-level primitives! Each object can be represented with a few tens of light-field-based primitives (c.f. 3DGS: hundreds+). w/ @cheng_yuzh21715 @XinKong_IC @paulhjkelly @AjdDavison
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(1/3) I am happy to share our work on Triangle Splatting SLAM! We show the first RGB-D SLAM to use differentiable triangles as a 3D map representation. Our method enables online mesh-based deformations and collision checking via on-the-fly Delaunay triangulation.
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(3/3) Delaunay triangulation allows us to recover thin connected structures like these branches. I find the deformations particularly satisfying.
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Nicholas Fry retweeted
Join us on 3 Jun. at 8 AM in Room 4EF for the On-Sensor Vision Workshop at @CVPR! #CVPR2026 onsensor-vision.github.io/ Through invited talks and posters, we’ll explore the future of on-sensor vision: low-power/latency edge computer vision enabled by sensor-side computation.
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