saurabhsaxena.bsky.social
@saurabhsaxena.bsky.social
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saurabhsaxena.bsky.social
saurabhsaxena.bsky.social @saurabhsaxena.bsky.social · Mar 5
Our team in Google DeepMind Toronto is hiring a Student Researcher for Summer 2025 to work on projects in Video generative models and 3D Computer Vision. If you are interested, please apply at: forms.gle/Yj1jmbvjBFQC...
Student Researcher, Google DeepMind in Generative Models and 3D Computer Vision
Location: Toronto Duration: 6 months Start date: Flexible in Spring/Summer 2025 Project Details: The project focuses on advancing generative modeling and/or computer vision techniques. The primary go...
forms.gle
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mtschannen.bsky.social
Michael Tschannen @mtschannen.bsky.social · Dec 2
Have you ever wondered how to train an autoregressive generative transformer on text and raw pixels, without a pretrained visual tokenizer (e.g. VQ-VAE)?

We have been pondering this during summer and developed a new model: JetFormer 🌊🤖

arxiv.org/abs/2411.19722

A thread 👇

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saurabhsaxena.bsky.social
saurabhsaxena.bsky.social @saurabhsaxena.bsky.social · Dec 3
SfM failing on dynamic videos? 😠 RoMo to the rescue! 💪 Our simple method uses epipolar cues and semantic features for robustly estimating motion masks, boosting dynamic SfM performance 🚀 Plus, a new dataset of dynamic scenes with ground truth cameras! 🤯 #computervision

🧵👇
lilygoli.bsky.social
Lily Goli @lilygoli.bsky.social · Dec 2
Hello everyone!! 👋
Excited to be here and share our latest work to get started!

RoMo: Robust Motion Segmentation Improves Structure from Motion

romosfm.github.io

Boost the performance of your SfM pipeline on dynamic scenes! 🚀 RoMo masks dynamic objects in a video, in a zero-shot manner.
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