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 recent #CVPR2025 paper AnyCam, a method for pose estimation in casual videos! 1️⃣ Can be directly trained on casual videos without the need for 3D annotation. 2️⃣ Based around a feed-forward transformer and light-weight refinement. ♦️ fwmb.github.io/anycam/

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!

🤗I’m excited to share our recent work: TwoSquared: 4D Reconstruction from 2D Image Pairs. 🔥 Our method produces geometry-consistent, texture-consistent, and physically plausible 4D reconstructions 📰 Check our project page sangluisme.github.io/TwoSquared/ ❤️ Zehranaz Canfes Riccardo Marin

I’m exited to share our work today at Hall 3 Singapore EXPO 3:00pm #ICLR2025 See you there.😄😄

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 🔥🔥🔥

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! ⬇️

Happy to support the #3DV2026 publicity efforts!

I'm beyond excited to share our latest work ✨️AlphaEvolve✨️, a Gemini-powered coding agent that designs advanced algorithms, tackling open mathematical challenges, and optimizing Google infrastructure (data centers, TPUs, AI training). Learn how 🚀: deepmind.google/discover/blog/…

#ICCV2025 AC thought: Part of being a responsible reviewer is engaging throughout the review process, not simply submitting your initial review. If you haven’t already, join your paper discussions.

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

Join us for a full-day 3D Shape Analysis tutorial at #CVPR2025 in Nashville, on Thursday, June 12, from 9:15 AM to 5:00 PM in Room 204! 👉 More details and the full schedule are available at: shape-analysis-tutorial.github.io/cvpr-25/

Many Congratulations to Jianyuan#CVPR2025 2025, Minghao Chen, Nikita Karaev, Andrea Vedaldi, Christian Rupprecht and David Novotny for winning the Best Paper Award @CVPR for "VGGT: Visual Geometry Grounded Transformer" 🥇🎉 🙌🙌 #CVPR2025!!!!!!

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

Let's make noise nonisotropic and inject connectivity prior into diffusion noise! Happening now, poster #158 TUM Computer Vision Group #CVPR2025

🦖 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.

Our paper "The Monado SLAM Dataset for Egocentric Visual-Inertial Tracking" has been accepted at #IROS2025! Because SLAM/VIO datasets were getting a bit too easy :) 🔗 huggingface.co/datasets/colla… 📄 arxiv.org/abs/2508.00088 🎥 youtu.be/-lsHpsTI-Q0 (1/5)