Nina Shvetsova

NeuralFur wins Best Paper Runner Up at @3DVconf. From multi-view images, we create a strand-based hair groom for animals. Unlike human hair, fur varies in length across the body parts of animals. NeuralFur leverages a VQA approach to infer fur lengths and directions across the body and to create a furless mesh. We then reconstruct strand-based fur geometry from multi-view images, resulting in a realistic animal model that is ready for physics-based animation in game engines like Unreal. Code is online. Check out the project page link below. Congratulations to @ness_pirs @bernakabadayi @AYiannakidis @gfgbec and @JustusThies! neuralfur.is.tue.mpg.de

Excited and deeply honored to receive the #3D Outstanding Doctoral Dissertation Award! 🏆 Huge thanks to the awards committee and to everyone making 3DV such a blast. And I couldn't be happier to share this recognition with my long-time friend and colleague @songyoupeng 🙌✨

Presenting M2SVid at #3DV2026 today! We tackle Monocular-to-Stereo Video conversion using a end-to-end inpainting and refinement pipeline. 📍 Poster Session 1 (10:15 - 12:00) 🚀 Code and models are now released! 🔗 m2svid.github.io 💻 github.com/google-researc… @3DVconf

🚨Call for Extended Abstracts for the WiCV Women in Computer Vision workshop at @CVPR 2026. Find all the details at: sites.google.com/view/wicv-cvpr… Submission Portal: #tab-your-consoles" target="_blank" rel="nofollow noopener">openreview.net/group?id=thecv… Deadline: 24 March 2026 #CVPR2026 #WiCV #ComputerVision

🎆 Wrapping up 2025 with a review of some exciting papers from our group 🎊 covering everything across audio-visual learning, explainability, bias mitigation & video understanding 🧵⬇️

🔗 Check it out: 👉 Project: m2svid.github.io 📄 Paper: arxiv.org/abs/2505.16565 💻 Code: (coming soon!) @3DVconf

📊 Results: ✅Higher Quality: Our approach outperforms previous state-of-the-art methods, being ranked best 2.6x more often than the second-place method in user studies. ✅Faster: Runs 6x faster than state-of-the-art competitors.

Excited to share our new paper: M2SVid: End-to-End Inpainting and Refinement for Monocular-to-Stereo Video Conversion! ACCEPTED by 3DV 2026!🎬 👉 Project: m2svid.github.io 📄 Paper: arxiv.org/abs/2505.16565 Done with Goutam Bhat, @prunetruong, @HildeKuehne, @fedassa 🧵👇

🌟Join us for the keynote with @HildeKuehne on 19th October, 1:55 pm at the WiCV workshop in Honolulu! #WiCV #WomeninComputerVision #ICCV2025 @ICCVConference

🚨🚨🚨Deadline <10 days 🚨🚨🚨 Submit your extended abstracts on AI driven comic analysis to the COMIQ workshop #ICCV2025 comiq-iccv25.github.io

@edsonroteia Thanks! ❤️

@ninashv__ Congrats on the release!

🚀 UTD is now fully released! Code ✅ Models ✅ 2M video descriptions ✅ Debiased splits for 12 datasets ✅ Everything you need to benchmark video models more fairly is now public: 🔗 github.com/ninatu/utd-pro… 🎥 Let’s make video understanding actually about video understanding.

Can diffusion models solve visual Sudoku? If you are at #ICML2025, come to our poster in the Wednesday morning poster session (Poster Session 3 East, Poster 3412) and find out! @ChrisWewer @bartek_pog Bernt Schiele @janericlenssen

🔗 Paper: arxiv.org/abs/2503.18637 🔗 Project: utd-project.github.io 🔗 Code & models: github.com/ninatu/utd-pro… (coming soon!) Done with @NagraniArsha Bernt Schiele @HildeKuehne Christian Rupprecht

Check out our @CVPR poster!🎉 🕓 June 15, 4–6 PM 🖼️ Poster #278 | 📍ExHall D Unbiasing through Textual Descriptions — we address representation bias in video benchmarks, releasing debiased splits for 12 datasets! Can’t present in person due to visa issues, but I’ll be online! 💻

Many Congratulations to @jianyuan_wang, @MinghaoChen23, @n_karaev, Andrea Vedaldi, Christian Rupprecht and @davnov134 for winning the Best Paper Award @CVPR for "VGGT: Visual Geometry Grounded Transformer" 🥇🎉 🙌🙌 #CVPR2025!!!!!!