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Jack (in SF) Langerman

@jacklangerman.bsky.social
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Jack (in SF) Langerman @jacklangerman.bsky.social · 03/06/2026
🎉Workshop On Urban Scene at @cvprconference.bsky.social modeling kicks off in less than 1 hr!!🎉 first up: @niessner.bsky.social ! You don't want to miss this one!! Mile high 3B
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Jack (in SF) Langerman @jacklangerman.bsky.social · 03/06/2026
We have arrived @cvprconference.bsky.social ! it's going to be a great week!
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Jack (in SF) Langerman @jacklangerman.bsky.social · 03/06/2026
@cvprconference.bsky.social
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Dmytro Mishkin @ducha-aiki.bsky.social · 02/06/2026
Tomorrow is a better day...because USM3D workshop at @cvprconference.bsky.social is happening? 6 keynote speakers. 2 challenges which I am finally not ashamed of? Debatable. Is it our final competition at HuggingFace? The only way to figure out is to attend. Mile High 3B. #CVPR2026
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Jack (in SF) Langerman @jacklangerman.bsky.social · 03/06/2026
🌟🌟 Start @CVPR off right with the Workshop on Urban Scene Modeling! (Tues Jun 2) @ Mile High 3B! 🌟 - Great lineup of key note speakers! - Challenge winners will be announced! - Selected paper talks! 3D/4D reconstruction+generation+understanding applied to the built world
Matthias Nießner
Florent Lafarge
Marc Pollefeys
Vasileios Balntas
Angel Xuan Chang
Daniel Barath

Workshop Schedule. Full day, June 3, Mile High 3B. 09:00–09:10 Welcome & introduction. 09:10–09:50 Keynote 1 — Matthias Nießner. 09:50–10:30 Building3D Challenge — winner talks. 10:30–10:45 Coffee break. 10:45–11:25 Keynote 2 — Florent Lafarge, “Two Decades of 3D Building Reconstruction: Paradigms, Progress, and Prospects.” 11:25–12:05 S23DR Challenge — winner talks. 12:05–13:00 Lunch. 13:00–13:40 Keynote 3 — Marc Pollefeys. 13:40–15:10 Paper Oral Presentation — 9 papers (next slide). 15:10–15:25 Coffee break. 15:25–16:05 Keynote 4 — Vasileios Balntas. 16:05–16:45 Keynote 5 — Angel Xuan Chang. 16:45–17:25 Keynote 6 — Daniel Barath. 17:25–17:55 Collaboration & Discussion (interactive panel). 17:55–18:00 Closing remarks.
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Dmytro Mishkin @ducha-aiki.bsky.social · 18/03/2026
Sad, but important announcement -- one of our challenges -- Building3D lost their sponsor in the very last moment. So new prize fund is $14k: - $12k for S23DR 2026 - $2k for Building3D 2026. We apologise for this situation, and hope that you still decide to participate. #CVPR2026
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Jack (in SF) Langerman @jacklangerman.bsky.social · 12/03/2026
ive taken to intentionally using endashes so i still get to use dash-based parentheticals, but astute observers will know it was "made by humans™"
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Dmytro Mishkin @ducha-aiki.bsky.social · 04/03/2026
Submit your paper of structured reconstruction -- CAD, semantic, wireframe, city monitoring, etc., to USM3D 2026! cmt3.research.microsoft.com/USM2026 Deadline: March 24, 2026. @cvprconference.bsky.social #CVPR2026 #USM3D2026 #USM3D
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Jack (in SF) Langerman @jacklangerman.bsky.social · 17/02/2026
at least the pytorch team triaged this one (that i found) and it got fixed github.com/pytorch/pyto... it really should be a priority though for sure - easy win imo
github.com
MPS compile off by 2x with broadcast and sum · Issue #170360 · pytorch/pytorch
🐛 Describe the bug Hey team, Looks like there is is a correctness issue with torch.compile when mode="default" on MPS for this simple broadcast and sum function. I'm seeing the output almost exactl...
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Jack (in SF) Langerman @jacklangerman.bsky.social · 04/02/2026
This was joint work with my wonderful colleagues Denis Rozumny, Yuzhong Huang, and @ducha-aiki.bsky.social and was presented at @iccv.bsky.social last year. bsky.app/profile/jack...
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Jack (in SF) Langerman @jacklangerman.bsky.social · 04/02/2026
🧵A bit last minute but I'm giving a talk tonight in SF about my work Explaining Human Preferences via Metrics for Structured 3D Reconstruction (ICCV Highlight) Quite near transamerica pyramid. Event is already full, but comment or shoot me a DM and we'll find a spot for you!
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Jack (in SF) Langerman @jacklangerman.bsky.social · 25/01/2026
me too plz✋️ looks great!
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Dmytro Mishkin @ducha-aiki.bsky.social · 24/10/2025
Come to our poster this afternoon starting at 2:30 (#214)
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Jack (in SF) Langerman @jacklangerman.bsky.social · 10/10/2025
What is the right metric to measure performance in structured 3D reconstruction? 🎬 Just posted the video for our @iccv.bsky.social #ICCV2025 highlight paper! 🎉 @jacklangerman.bsky.social, Denys Rozumnyi, Yuzhong Huang, @ducha-aiki.bsky.social 🌄 iccv.thecvf.com/virtual/2025...
youtu.be
[ICCV 2025] Explaining Human Preferences via Metrics for Structured Reconstruction - ICCV Highlight
YouTube video by Jack Langerman
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Jack (in SF) Langerman @jacklangerman.bsky.social · 22/09/2025
i mean the 1-3 minute version
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Jack (in SF) Langerman @jacklangerman.bsky.social · 22/09/2025
what makes a good paper video? what are some of the best you have seen? cc: @davidpicard.bsky.social @davidbau.bsky.social @eugenevinitsky.bsky.social @chriswolfvision.bsky.social @nsaphra.bsky.social @ducha-aiki.bsky.social @parskatt.bsky.social @martin-r-oswald.bsky.social @ericzzj.bsky.social
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Jack (in SF) Langerman @jacklangerman.bsky.social · 13/09/2025
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Jack (in SF) Langerman @jacklangerman.bsky.social · 13/09/2025
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Jack (in SF) Langerman @jacklangerman.bsky.social · 25/06/2025
Very proud that our paper has been accepted to @iccv.bsky.social !!! See you in Hawaii! bsky.app/profile/duch...
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Zhenjun Zhao @ericzzj.bsky.social · 09/05/2025
🎉 Thrilled to share our CVPR 2025 Award Candidate & Oral paper: 🔹 GlobustVP Convex Relaxation for Robust Vanishing Point Estimation in Manhattan World 🧱 Global optimality 💥 Tolerates up to 70% outliers ⚡ Fast runtime 📄 Paper: arxiv.org/abs/2505.04788 💻 Code: github.com/WU-CVGL/GlobustVP 1/
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#ICCV2025 @iccv.bsky.social · 09/05/2025
#ICCV2025 reviews are out and being sent via email to authors! They will also be available on OpenReview later. 11,152 active submissions all have at least 3 reviews. Authors have the opportunity to submit a rebuttal by May 16 2025 11:59 PM HST.
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Jack (in SF) Langerman @jacklangerman.bsky.social · 07/05/2025
Please reshare, tell you friends, give it a try, and don't hesitate to reach out to the team with any questions! bsky.app/profile/jack...
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Jack (in SF) Langerman @jacklangerman.bsky.social · 07/05/2025
🌍 Workshop + other challenges at: usm3d.github.io Let’s make SfM more structured. Good luck, teams! (7/7)
usm3d.github.io
2nd Workshop on Urban Scene Modeling: Where Vision Meets Photogrammetry and Graphics
CVPR 2025 Workshop on Urban Scene Modeling: Where Vision Meets Photogrammetry and Graphics.
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Jack (in SF) Langerman @jacklangerman.bsky.social · 07/05/2025
📌 Want a clear reference? Check out the example baseline submission: huggingface.co/usm3d/handcr... (6/7)
huggingface.co
usm3d/handcrafted_submission_2025 · Hugging Face
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
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Jack (in SF) Langerman @jacklangerman.bsky.social · 07/05/2025
📊 NEW Evaluation Metric Say goodbye to WED. Hello to a human-aligned combo of: • Vertex F1 • Edge IoU Backed by this paper: 👉 arxiv.org/abs/2503.08208
arxiv.org
Explaining Human Preferences via Metrics for Structured 3D Reconstruction
"What cannot be measured cannot be improved" while likely never uttered by Lord Kelvin, summarizes effectively the purpose of this work. This paper presents a detailed evaluation of automated metrics ...
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Jack (in SF) Langerman @jacklangerman.bsky.social · 07/05/2025
⚙️ All helper functions + data loaders: pip install hoho2025 🛠️ Codebase: github.com/s23dr/hoho2025 (4/7)
github.com
GitHub - s23dr/hoho2025: Tools and utilities for the S23DR-2025 competition and HoHo25k Dataset
Tools and utilities for the S23DR-2025 competition and HoHo25k Dataset - s23dr/hoho2025
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Jack (in SF) Langerman @jacklangerman.bsky.social · 07/05/2025
📦 New dataset: hoho25k — 5x bigger than 2024! • 25,000 scenes • 8 images per scene • 200,000 total images 📥 Get it here: huggingface.co/datasets/usm... (3/7)
huggingface.co
usm3d/hoho25k · Datasets at Hugging Face
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
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Jack (in SF) Langerman @jacklangerman.bsky.social · 07/05/2025
🧠 The task: Turn multiview inputs (semantic segs, monocular depth) + SfM outputs (point clouds + camera poses) into sparse, geometrically accurate wireframes. AKA: “More Structured Structure-from-Motion” 😎 Challenge page 👉 huggingface.co/spaces/usm3d... (2/7)
huggingface.co
S23DR2025 - a Hugging Face Space by usm3d
This application allows you to view competition details, manage your submissions, and check leaderboards. You can access rules, dataset information, and view your own submissions and scores.
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Jack (in SF) Langerman @jacklangerman.bsky.social · 07/05/2025
🚨 Just one month left to submit your solutions for The Structured Semantic 3D Reconstruction (S23DR-2025) Challenge!!! It is not too late to join! Comp on @hf.co, part of the Workshop on Urban Scene Modeling at @cvprconference.bsky.social 2025 🔥$25,000 prize pool. Deadline: June 5, 2025. 🧵 (1/7)
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Jack (in SF) Langerman @jacklangerman.bsky.social · 30/04/2025
hey @cloneofsimo.bsky.social (or anyone else) did you ever try LoRA+ style LR split between down/up LoRA projection matrices on diffusion models?
LoRA+: Efficient Low Rank Adaptation of Large Models

Soufiane Hayou, Nikhil Ghosh, Bin Yu
In this paper, we show that Low Rank Adaptation (LoRA) as originally introduced in Hu et al. (2021) leads to suboptimal finetuning of models with large width (embedding dimension). This is due to the fact that adapter matrices A and B in LoRA are updated with the same learning rate. Using scaling arguments for large width networks, we demonstrate that using the same learning rate for A and B does not allow efficient feature learning. We then show that this suboptimality of LoRA can be corrected simply by setting different learning rates for the LoRA adapter matrices A and B with a well-chosen ratio. We call this proposed algorithm LoRA+. In our extensive experiments, LoRA+ improves performance (1-2 % improvements) and finetuning speed (up to ∼ 2X SpeedUp), at the same computational cost as LoRA.
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Aaron Mueller @amuuueller.bsky.social · 23/04/2025
Lots of progress in mech interp (MI) lately! But how can we measure when new mech interp methods yield real improvements over prior work? We propose 😎 𝗠𝗜𝗕: a 𝗠echanistic 𝗜nterpretability 𝗕enchmark!
Logo for MIB: A Mechanistic Interpretability Benchmark
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Jack (in SF) Langerman @jacklangerman.bsky.social · 27/03/2025
When I was working at Bell Labs in Murray Hill we used to specifically go to 3rd floor for coffee because the couch in that particular coffee room was (supposedly) Dennis Ritchie's. was also a room with a whiteboard that may have been where Shannon did a lot of the info theory work. good times
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Jack (in SF) Langerman @jacklangerman.bsky.social · 18/03/2025
do you think this is a matter of semantic disipline or genuine beliefs about qualia? ie "with certain inputs models can produce outputs that contain patterns typically associated with anxiety in humans. asking them to perform mindfulness exercises can mitigate this behavior" vs "they feel anxious"?
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Dmytro Mishkin @ducha-aiki.bsky.social · 17/03/2025
1 week to USM3D deadline
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Jack (in SF) Langerman @jacklangerman.bsky.social · 15/03/2025
more blending between rings i think (~long range dependence)
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Dmytro Mishkin @ducha-aiki.bsky.social · 12/03/2025
Explaining Human Preferences via Metrics for Structured 3D Reconstruction @jacklangerman.bsky.social Denys Rozumnyi, Yuzhong Huang, @ducha-aiki.bsky.social tl;dr: we asked 3D modelers to rank wireframe reconstructions & compared it to ranking by metrics. Observations🧵 1/ arxiv.org/abs/2503.08208
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Dmytro Mishkin @ducha-aiki.bsky.social · 10/03/2025
2nd Building3D #CVPR2025 challenge at #USM3D workshop is open! Task: point cloud to wireframe. Prize pool: $10k Competition deadline: May 25 2025. Website: huggingface.co/spaces/Build... @cvprconference.bsky.social
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Johan Edstedt @parskatt.bsky.social · 10/03/2025
We made a new keypoint detector named DaD, paper isn't up yet, but code and weights are: github.com/Parskatt/dad
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Dmytro Mishkin @ducha-aiki.bsky.social · 10/03/2025
Those, who work in structured (images/pcl to CAD) reconstruction - USM3D #CVPR2025 workshop submissions are open. Deadline: March 24 2025 Both full papers (8 pages) and extended abstracts (4 pages) are OK usm3d.github.io #USM3D @cvprconference.bsky.social @jacklangerman.bsky.social
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Dmytro Mishkin @ducha-aiki.bsky.social · 09/03/2025
We have extended the deadline for paper submission for Image Matching Workshop. Anything image matching or 3D reconstruction related is welcomed Now it is March 17 @cvprconference.bsky.social #CVPR2025 image-matching-workshop.github.io
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Jack (in SF) Langerman @jacklangerman.bsky.social · 06/03/2025
github.com/pytorch/pyto...
github.com
MPS operator coverage tracking issue (2.6+ version) · Issue #141287 · pytorch/pytorch
🐛 Describe the bug This issue is to have a centralized place to list and track work on adding support to new ops for the MPS backend. PyTorch MPS Ops Project : Project to track all the ops for MPS ...
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Jack (in SF) Langerman @jacklangerman.bsky.social · 06/03/2025
yeah `PYTORCH_ENABLE_MPS_FALLBACK=1 python myscript.py` did it.
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Jack (in SF) Langerman @jacklangerman.bsky.social · 06/03/2025
bsky.app/profile/jack...
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Jack (in SF) Langerman @jacklangerman.bsky.social · 06/03/2025
oh no....
:_( 
operation not implemented on MPS
woe is me...
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Jack (in SF) Langerman @jacklangerman.bsky.social · 31/01/2025
what is the best intro I can send people who suddenly want to know "what is AI?" and "what is a transformer based model?" but arent really going to invest tons of time and maybe dont have any math background? my default is 3b1b, but does anyone have another suggestion?
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Dmytro Mishkin @ducha-aiki.bsky.social · 02/01/2025
Image matching and ChatGPT - new post in the wide baseline stereo blog. tl;dr: it is good, even feels like human, but not perfect. ducha-aiki.github.io/wide-baselin...
ducha-aiki.github.io
ChatGPT and Image Matching – Wide baseline stereo meets deep learning
Are we done yet?
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Jack (in SF) Langerman @jacklangerman.bsky.social · 29/12/2024
ive said for a long time this is one of the things I love most about ML: get to play in everyones' playgrounds :-)
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Jack (in SF) Langerman @jacklangerman.bsky.social · 27/12/2024
o u know - jc
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Jack (in SF) Langerman @jacklangerman.bsky.social · 27/12/2024
Alcohol
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Jack (in SF) Langerman @jacklangerman.bsky.social · 21/12/2024
Yeah, definitely a healthy amount of uncertainty here, but somehow feels related to bsky.app/profile/jack... Maybe we just don't have the right optimizer or something, so we need the easy to train big model to "simplify" for the small (harder to optimize) model, but for sure a bit of a mystery
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