🔥The 9th Round of Easy Loan, Earn $40 Reward is in progress❗️ ⏰ Promotion Period: January 15th - Feburary 15th, 2025 👉 Register now and check more details at gate.io/campaigns/358

Introducing LoftUp! A stronger (than ever) and lightweight feature upsampler for vision encoders that can boost performance on dense prediction tasks by 20%–100%! Easy to plug into models like DINOv2, CLIP, SigLIP — simple design, big gains. Try it out! github.com/andrehuang/lof…

Check out our latest #CVPR2025 work AnyCam! Instead of relying on videos with 3D annotations, AnyCam learns pose estimation directly from unlabeled dynamic videos. This is an interesting alternative to methods like Monst3r, which rely on expensive pose labels during training!

Back on Track: Bundle Adjustment for Dynamic Scene Reconstruction Weirong Chen, Ganlin Zhang, Felix Wimbauer @ CVPR2025, Rui Wang, Nikita Araslanov, Andrea Vedaldi, Daniel Cremers tl;dr: learning-based 3D point tracker decouples camera and object-based motion arxiv.org/abs/2504.14516

Back on Track: Bundle Adjustment for Dynamic Scene Reconstruction Weirong Chen, Ganlin Zhang, Felix Wimbauer @ CVPR2025 , Rui Wang, Nikita Araslanov Andrea Vedaldi, Daniel Cremers tl;dr even for non-rigid SfM you can do BA on static parts -> improves everything. arxiv.org/abs/2504.14516

Check out how AnyCam is using Rerun viz on their project page 🔥🔥🔥

🚀Excited to announce our #CVPR2025 2025 paper: Unbiasing through Textual Descriptions! We release UTD-descriptions for 1.9M videos and object-debiased splits for 12 datasets! 🔗Project: utd-project.github.io Arsha Nagrani Bernt Schiele Hilde Kuehne Christian Rupprecht 🧵👇

Paper of today: Pataki et al., "MP-SfM: Monocular Surface Priors for Robust Structure-from-Motion" -- github.com/cvg/mpsfm Depth estimators work great. Time to integrate them into SfM pipelines.

Can you train a model for pose estimation directly on casual videos without supervision? Turns out you can! In our #CVPR2025 paper AnyCam, we directly train on YouTube videos and achieve SOTA results by using an uncertainty-based flow loss and monocular priors! ⬇️

Excited to share ☀️Lightspeed⚡, a photorealistic, synthetic dataset with ground truth pose used for benchmarking alongside DynPose-100K! Now available for download: huggingface.co/datasets/nvidi… Paper accepted to #CVPR2025: arxiv.org/abs/2504.17788

Happy to support the #3DV2026 publicity efforts!

Full draft of the SLAM Handbook now released --- available as a free PDF, with a printed version coming soon. Now including Part 3, "From SLAM to Spatial AI" (I knew it would catch on eventually), with contributions from Hide and me. #SpatialAI github.com/SLAM-Handbook-…

Can we match vision and language representations without any supervision or paired data? Surprisingly, yes!  Our #CVPR2025 paper with Nikita Araslanov and Daniel Cremers shows that the pairwise distances in both modalities are often enough to find correspondences. ⬇️1/4

This Saturday at CVPR, don't miss Oral Session 3A. Vision all-stars Qianqian Wang, Linyi Jin, Zhengqi Li are presenting MegaSaM, CUT3R, and Stereo4D. The posters are right after, and the whole crew will be there. It'll be fun. Drop by.

Looking forward to presenting our paper "Finsler multi-dimensional scaling" at #CVPR2025 on Sunday 10:30am, Poster 462! We investigate a largely uncharted research direction in computer vision, aka Finsler manifolds...

Excited to be attending CVPR 2025 this week in Nashville! I’ll be presenting our recent work: “4Deform: Neural Surface Deformation for Robust Shape Interpolation” 📍 Poster session: [13th June 4pm-6pm poster #111] #CVPR2025 #computervision

Bolt3D is accepted to #ICCV2025 🥳 see you in Hawaii!

🦖 We present “Feed-Forward SceneDINO for Unsupervised Semantic Scene Completion”. #ICCV2025 🌍: visinf.github.io/scenedino/ 📃: arxiv.org/abs/2507.06230 💻: github.com/tum-vision/sce… 🤗: huggingface.co/spaces/jev-ale… w/ A. Jevtić Felix Wimbauer @ CVPR2025 Oliver Hahn C. Rupprecht Stefan Roth D. Cremers

We're back this summer with ZurichCV#10 on the 7th of August at the ETH AI Center! Felix Wimbauer (TUM) will talk about 3D scene understanding and Joan Puigcerver (DeepMind) about scaling computer vision architectures. RSVP below.