Selena Ling 凌子涵 @seleniumlzh
U of Toronto CS PhD at DGP | Prev. @AdobeResearch @NVIDIA : ) iszihan.github.io Toronto, Canada Joined August 2012-
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Selena Ling 凌子涵 retweeted
📢 Lyra: Generative 3D Scene Reconstruction via Video Diffusion Model Self-Distillation Got only one or a few images and wondering if recovering the 3D environment is a reconstruction or generation problem? Why not do it with a generative reconstruction model! We show that a…
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Selena Ling 凌子涵 retweeted
📢📢📢 3D Gaussian Flats @ #NeurIPS2025 A hybrid 2D/3D representation that reconstructs photorealistic scenes. 🔗 Project: theialab.github.io/3dgs-flats 📄 ArXiv: arxiv.org/abs/2509.16423 💻 Code: github.com/theialab/3dgs-…
Selena Ling 凌子涵 retweeted
Season 1 of Toronto School of Foundation Modelling kicks off this Thursday at New Stadium!!! 60 people will be attending weekly sessions for 3 months, learning to build Foundation Models from scratch. Around 10 guest speakers (more to come) will be flying to Toronto to talk…
Season 1 of Toronto School of Foundation Modelling kicks off this Thursday at New Stadium!!! 60 people will be attending weekly sessions for 3 months, learning to build Foundation Models from scratch. Around 10 guest speakers (more to come) will be flying to Toronto to talk…
Selena Ling 凌子涵 retweeted
I’m excited to announce that our paper, “Learning Riemannian Metrics for Interpolating Animations,” has been accepted to GSI 2025! 🧵 co-authored with @vm2358 at @UofT and @ninamiolane at the @UCSB @geometric_intel lab! gi.ece.ucsb.edu/node/217
Selena Ling 凌子涵 retweeted
“Everyone knows” what an autoencoder is… but there's an important complementary picture missing from most introductory material. In short: we emphasize how autoencoders are implemented—but not always what they represent (and some of the implications of that representation).🧵
Selena Ling 凌子涵 retweeted
Check out our new paper on robust motion segmentation! Wanna run your SfM pipeline on dynamic scenes? Consider using our RoMo masks to get improvements!! 🚀
Check out our new paper on robust motion segmentation! Wanna run your SfM pipeline on dynamic scenes? Consider using our RoMo masks to get improvements!! 🚀
Selena Ling 凌子涵 retweeted
For folks in the @siggraph community: You may or may not be aware of the controversy around the next #SIGGRAPHAsia location, summarized here: cs.toronto.edu/~jacobson/webl… If you're concerned, consider signing this letter: docs.google.com/document/d/1ZS… via this form docs.google.com/forms/d/e/1FAI…
Selena Ling 凌子涵 retweeted
Total Pixel Space, which won the Grand Prix at this year's AIFF, is a wonderful video essay and, by the way, one of the clearest descriptions of universal simulation (as search in the space of all possible universes) youtube.com/watch?v=zpAeyg…
Selena Ling 凌子涵 retweeted
Our work was featured by MIT News today! Had so much fun working on this project with Silvia Sellán, Natalia Pacheco-Tallaj and @JustinMSolomon. Can't wait to present it at SIGGRAPH this summer! news.mit.edu/2025/animation…
Selena Ling 凌子涵 retweeted
📢📢📢 Neural Inverse Rendering from Propagating Light 💡 Our CVPR Oral introduces the first method for multiview neural inverse rendering from videos of propagating light, unlocking applications such as relighting light propagation videos, geometry estimation, or light…
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