adil meric

@SGiebenhain @Uber_Support @Uber_Brasil @Uber_Support @Uber_Brasil

@Uber_Support @Uber_Brasil urgent help needed! I left my luggage in an Uber in Rio with my passport inside. I’ve already filed a report in the app, but the driver isn’t responding. I’m a tourist and need to fly back to Germany. Can you help me reach him? 🙏

📢Face Anything: 4D Face Reconstruction from Any Image Sequence Transformer model for 4D face reconstruction and dense tracking: - predict canonical facial coordinates per pixel - tracking as reconstruction in canonical space - geometry + correspondences in one forward pass Key idea: a shared canonical space across frames - correspondences as nearest neighbors - no motion or deformation estimation Stable geometry and tracking, even under large expressions and viewpoint changes - check out our results! 🌐 kocasariumut.github.io/FaceAnything ▶️ youtu.be/wSGHpAscp0Y Great work by @UmutKocasa4344, @SGiebenhain, @richard_o_shaw

@yawarnihal @ErkocZiya 🚀🚀🚀

Check out @ErkocZiya 's work on planning for scene generation!

@d_yesiltepe 🚀 🚀 🚀

Infinity-RoPE is accepted to #CVPR2026🎉! ✨In Infinity-RoPE, we extend pretrained autoregressive video models beyond the temporal RoPE limit, enabling the generation of effectively infinite-length videos while maintaining strong responsiveness to action prompts and supporting cinematic scene transitions, all without additional training. Kudos to the team: @tunahansalih @akaan_akan @kaan_oktay @PINguAR and @fal 🌐 Project Page: infinity-rope.github.io

Very cool!

Releasing Echo today is incredibly exciting for me — because it is a critical step for generative AI, enabling the creation of virtual worlds. Echo is our first world model at SpAItial AI. It turns text or images into explorable 3D environments — spaces you can move through, inspect, and build on. Seeing this work in real time still feels a bit surreal. My fascination with this goes back a long way: video games, virtual environments, and the idea of capturing the real world in 3D. As a researcher, I spent years working on 3D reconstruction, neural rendering, and scene understanding — all driven by the same question: how do we teach machines to understand the world? One thing became clear over time: the biggest bottleneck isn’t compute or rendering — it’s 3D worlds themselves. High-quality, consistent environments are expensive to create by hand and don’t scale to the experiences we want to build. In particular, I believe that the ability to generate virtual worlds is ultimately key towards understanding the real world. That’s why we founded SpAItial AI. We’re building spatial world models that combine geometric understanding with creative generation — models that can generate, edit, and eventually reason about 3D environments. Echo is just the beginning. For me, this feels like the moment when decades of research finally meet the imagination that got many of us into graphics, games, 3D understanding in the first place.🌍 spaitial.ai

Excited to share that our paper “Error Broadcast and Decorrelation as a Potential Artificial and Natural Learning Mechanism”—with @CPehlevan and @Alper_T_E—was accepted as a #NeurIPS2025 Spotlight! 🎉 Paper:🔗 arxiv.org/pdf/2504.11558

@taiyasaki Very cool topics and lineup of speakers! Could we get access to the presentations? Are you planning to share them?

Just a few seats left in the GeoFreeNVS workshop at #ICCV2025 (Room: 323 C) Right now Yin Cui from NVIDIA is presenting Cosmos! geofreenvs.github.io

"The Tower Heist" A small window is open to recover an ancient scroll. Created in early access with the fantastic new @Kling_ai 2.5 Turbo model bringing affordable generations with best in class prompt adherence and quality. The range of directed character motions now available to us is incredible! 🔊🔊🎧

Presenting PrEditor3D at #CVPR2025 📢📢 If you'd like to learn more about our work and discuss 3D generation/editing, come visit our poster on Friday, June 13th, in ExHall D between 10:30-12:30 (Poster #44). Project Page: ziyaerkoc.com/preditor3d

Totally agree. Gymnastics, street dance and close human interaction are impossible to generate with any video generation model. A new bar has been set…

🌟 Research Update We introduce FluxSpace, a new method for manipulating the image semantics in rectified flow transformers in a disentangled way! Shoutout to my collaborator @kavanav2912 and my advisor @PINguAR

🚀 Excited to share our latest work, MotionShop, a training-free approach for motion transfer in video diffusion models! 🎥 Big thanks to my amazing teammates from GEMLAB—@tunahansalih, Connor Dunlop, and @PINguAR—for making this possible! 🙌 🌐 motionshop-diffusion.github.io

📢📢 𝐏𝐫𝐄𝐝𝐢𝐭𝐨𝐫𝟑𝐃: 𝐅𝐚𝐬𝐭 𝐚𝐧𝐝 𝐏𝐫𝐞𝐜𝐢𝐬𝐞 𝟑𝐃 𝐒𝐡𝐚𝐩𝐞 𝐄𝐝𝐢𝐭𝐢𝐧𝐠 📢📢 We propose a training-free 3D shape editing approach that rapidly and precisely edits the regions intended by the user and keeps the rest as is. Using a quickly brushed mask and a text prompt, we first apply multi-view editing in the 2D domain and then run our merging algorithm in the 3D feature space to ensure that the edited shape is loyal to the input shape. Project Page: ziyaerkoc.com/preditor3d/ Video: youtube.com/watch?v=Ty2xXa… Great work by @ErkocZiya @cangumeli Chaoyang Wang @angelaqdai @peter_wonka @hyjameslee @PeiyeZ

Introducing the first NeRF-based 3D style transfer method that generalizes across scenes and styles! Our approach eliminates the time-consuming optimization for each scene or style, making it more efficient than previous NeRF-based methods. Check it out! #GCPR2024

G3DST: Generalizing 3D Style Transfer with NeRF across Scenes and Styles! Given a style latent, our hypernetwork estimates MLP params that transform aggregated ray features. mericadil.github.io/G3DST/ Great work by our MA student @adilmeric12 U. Kocasari @barbara_roessle #GCPR24

Thrilled to introduce our latest research at the upcoming #NeurIPS DGM4H workshop this December: “flowVI: Flow Cytometry Variational Inference” 🥳👨‍💻🧬. Many thanks to @fabian_theis @LM_Koenig @adilmeric12 @HelmholtzMunich. Dive into our full paper 📰: doi.org/10.1101/2023.1…

Research summary for the last 3 years... 2021: Replace every CNN with a Transformer 2022: Replace every GAN with diffusion models 2023: Replace every NeRF with Gaussian splatting

AI generative fill extending famous animal memes by parh0 instagram: instagram.com/p/CtY6smpId81/