Johan Edstedt's Avatar

Johan Edstedt

@parskatt.bsky.social

PhD student @ Linköping University I like 3D vision and training neural networks. Code: https://github.com/parskatt Weights: https://github.com/Parskatt/storage/releases/tag/roma

1,640 Followers  |  418 Following  |  1,991 Posts  |  Joined: 16.11.2024
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Posts by Johan Edstedt (@parskatt.bsky.social)

Post image 09.03.2026 00:00 — 👍 5    🔁 0    💬 1    📌 0

If only there was a benchmark bigger than 37 pairs... Alas.

08.03.2026 14:33 — 👍 3    🔁 0    💬 1    📌 0
Post image

Coming soon

07.03.2026 05:10 — 👍 18    🔁 0    💬 1    📌 0

Et tu3r

06.03.2026 16:38 — 👍 0    🔁 0    💬 0    📌 0

Putting a vowel before 3R should be illegal.

06.03.2026 15:03 — 👍 3    🔁 0    💬 3    📌 0
Post image 05.03.2026 18:26 — 👍 9    🔁 0    💬 0    📌 0
Post image 05.03.2026 18:18 — 👍 23    🔁 0    💬 0    📌 0
Post image 05.03.2026 17:16 — 👍 13    🔁 0    💬 1    📌 0

Want to mention that I don't think schedules are always bad... It does tend to be the case that lowering learning rate puts you in regions with higher gradients., which can lead to spikes. On the other hand, higher lr means more instability.

23.02.2026 20:55 — 👍 2    🔁 0    💬 2    📌 0

Edstedtian Representation Hypothesis.

18.02.2026 07:30 — 👍 0    🔁 0    💬 1    📌 0

You're on the exponential curve.

09.02.2026 15:52 — 👍 1    🔁 0    💬 1    📌 0

Nope, more scenes.

09.02.2026 12:07 — 👍 1    🔁 0    💬 1    📌 0

Other than being lefthanded it makes sense ;^)

07.02.2026 07:35 — 👍 0    🔁 0    💬 0    📌 0
Post image 06.02.2026 22:05 — 👍 8    🔁 0    💬 1    📌 0

This is just big wheat propaganda, flour cant scale.

05.02.2026 07:44 — 👍 0    🔁 0    💬 0    📌 0

Take me down to the Parallax city where the far moves slow and the near moves quickly

01.02.2026 15:40 — 👍 16723    🔁 4841    💬 94    📌 73

"a lazy human would not ignore all prior art" idk, the papers I've reviewed say otherwise ;)

02.02.2026 07:47 — 👍 2    🔁 0    💬 1    📌 0

I might try some approaches this weekend.

30.01.2026 16:46 — 👍 2    🔁 0    💬 0    📌 1

My guess is that:

1. COLMAP would work pretty well (with good corresp), but baseline is rather small, and dynamics of cloud would be tricky.

2. Feed-forward methods would underestimate the size of the cloud.

Interested if this is indeed the case, or my intuitions are wrong.

30.01.2026 13:11 — 👍 3    🔁 0    💬 1    📌 0

Is there any current 3/4D reconstruction method able to accurately reconstruct this scene? (with correct size of thunderstorm)

30.01.2026 13:08 — 👍 16    🔁 1    💬 3    📌 0

regardless of your views on AI, i strongly agree with this viewpoint! you are not funded by taxpayers to optimize your knowledge consumption workflows. it's good that you enjoy your job, you are getting paid to enjoy your job

26.01.2026 18:35 — 👍 5    🔁 0    💬 0    📌 0

Should the rebuttal contain the updated paper ID?

For revising after the OpenReview debacle we were not supposed to do so.

22.01.2026 18:32 — 👍 2    🔁 0    💬 1    📌 0

Sounds like it was "on time" by sj standards.

22.01.2026 09:30 — 👍 1    🔁 0    💬 1    📌 0

You have days like these, but also days where it looks like Mordor.

22.01.2026 09:15 — 👍 2    🔁 0    💬 1    📌 0
21.01.2026 16:09 — 👍 6    🔁 1    💬 0    📌 0

hehe, we'll see what I have time for.

16.01.2026 16:12 — 👍 2    🔁 0    💬 0    📌 0

Sure, but the DeDoDe descriptor would perform very well with 4k keypoints for another detector, such as ALIKED or DaD :)
I would bet that we would beat their IMC22 numbers in that setting.

16.01.2026 15:50 — 👍 1    🔁 0    💬 0    📌 0
Post image

If you run the dedode descriptor with dad keypoints you generally get much better results for lower number of keypoints than the original detector. (Shown is dedode descriptions matched with different detectors).

16.01.2026 15:47 — 👍 1    🔁 0    💬 1    📌 0

Yes, likely. We ran with 30k keypoints (or whatever gave the best performance). You can see that our results for other descriptors is also in general better.

16.01.2026 15:45 — 👍 1    🔁 0    💬 2    📌 0
Post image 16.01.2026 13:02 — 👍 2    🔁 0    💬 1    📌 0