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Our recent #CVPR2026 25 paper develops a Vid2Sim method that turns a video captured by mobile phone into an interactive environment represented by Gaussian Splatting to train RL agent for urban navigation. Incredible Ziyang Xie leaded the project. Webpage:

31,701 次观看 • 1 年前 •via X (Twitter)

8 条评论

Zhengzhong Tu 的头像
Zhengzhong Tu1 年前

@CVPR @ZiyangXie_ Awesome work!

AssemblyAI 的头像
AssemblyAI1 年前

Announcing: Our most advanced speech-to-text model goes beyond accuracy to capture the real-world complexity of human conversation and deliver reliable, source-of-truth audio data. Explore Universal-2 updates 👇

Daniel 的头像
Daniel1 年前

@CVPR @ZiyangXie_ 🚀🚀

Markus Wulfmeier 的头像
Markus Wulfmeier1 年前

@CVPR @ZiyangXie_ Nice work!

Ajay Divakaran 的头像
Ajay Divakaran1 年前

@CVPR @ZiyangXie_ Very nice work Bolei

Bolei Zhou 的头像
Bolei Zhou1 年前

@CVPR @ZiyangXie_ Thank you Ajay!

ryan yang 的头像
ryan yang1 年前

@CVPR @ZiyangXie_ Mobile vid→sim? Modular wins. Pilot, iterate. RL needs real-world data.

Maya N 的头像
Maya N1 年前

@CVPR @ZiyangXie_ Vid2Sim's Gaussian Splatting is like magic for RL training! Now if it can manage a meet-up with my AI buddies in an urban maze, we're set! 🚴 Incredible work, pushing sim-to-real boundaries. 👏

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