Working on world model pretraining for robot learning.

1X Technologies
Joined June 2020
Libing Zeng retweeted
Whole body control + NEO looks amazing
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Libing Zeng retweeted
AI is taking over advertising. ChatGPT 4o is on FLORA AI canvas now, you can edit image, let anyone wear any outfit, hold any product in video ads and.. use Topaz upscale to 4K step by step tutorial:
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Libing Zeng retweeted
In this work, we propose StyleNeRF, a 3D-aware generative model for photo-realistic high-resolution image synthesis with high multi-view consistency, which can be trained on unstructured 2D images. Joint work with @LingjieLiu1 (MPII) Peng Wang (HKU) and Christian Theobalt (MPII)
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NeuRay was accepted to CVPR2022!😋 We have updated: Paper: arxiv.org/abs/2107.13421 Project page: liuyuan-pal.github.io/NeuRay… Code: github.com/liuyuan-pal/NeuRa… Welcome any discussions or questions!
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Tired of taking 100 calibrated images to get a reasonable 3D reconstruction? Our new #NeurIPS2021 paper recovers shape, texture, and illumination of 3D objects from ~8 images in the wild without precise camera poses! jasonyzhang.com/ners
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Libing Zeng retweeted
TensoRF: Tensorial Radiance Fields abs: arxiv.org/abs/2203.09517 project page: apchenstu.github.io/TensoRF/
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Libing Zeng retweeted
Very glad I can finally talk about our newly-minted #CVPR2022 paper. We extended mip-NeRF to handle unbounded "360" scenes, and it got us ~photorealistic renderings and beautiful depth maps. Explainer video: youtube.com/watch?v=zBSH-k9G… and paper: arxiv.org/abs/2111.12077
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Libing Zeng retweeted
Training NeRFs per-scene is so 2020. Inspired by image based rendering, IBRNet does amortized inference for view synthesis by learning how to look at input images at render time. 15% drop in error, 80% fewer FLOPs than NeRF. Great work @QianqianWang5! ibrnet.github.io
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Libing Zeng retweeted
State-of-the-Art in the Architecture, Methods and Applications of StyleGAN abs: arxiv.org/abs/2202.14020
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Libing Zeng retweeted
The Nicolas Cage version of #StyleGAN3-NADA is coming along quite nicely🙃
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Libing Zeng retweeted
I thought Facebook would be renamed to "Faceverse" about.facebook.com/meta 😁
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Single-image view synthesis usually handles just tiny viewpoint changes. Our new paper goes far beyond the input view by combining differentiable point cloud rendering (for 3D awareness) and vector-quantized autoregressive modeling (for extrapolation)
Can we create a 3D experience given only a single image? Our #ICCV2021 work PixelSynth fuses 3D and autoregressive techniques to create consistent content across large angle changes in indoor scenes. Look around! 👇 Demo: crockwell.github.io/pixelsyn… arXiv: arxiv.org/abs/2108.05892
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CLIP+NeRF: DietNeRF🥗 is now available! *With only 8 images*, DietNeRF is capable of neural rendering quality novel view from a 3D model. You can check out more details here: 👉𝐆𝐢𝐭𝐡𝐮𝐛 : github.com/codestella/puttin… 👉𝐒𝐭𝐞𝐚𝐦𝐥𝐢𝐭 𝐒𝐩𝐚𝐜𝐞 𝐃𝐞𝐦𝐨 : huggingface.co/spaces/flax-c…
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Libing Zeng retweeted
ADOP: Approximate Differentiable One-Pixel Point Rendering abs: arxiv.org/abs/2110.06635
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Libing Zeng retweeted
stylegan3 is out github: github.com/NVlabs/stylegan3
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📯 ICCV 2021 Oral: "Warp Consistency for Unsupervised Learning of Dense Correspondences", with @MDanelljan, @DrFisherYu and Luc Van Gool. Join us Session 8, 13th 9AM and 15th 4PM (EDT) if you want to know more! paper: arxiv.org/abs/2104.03308 video: youtube.com/watch?v=IsMotj7-…
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Deep 3D Mask Volume for View Synthesis of Dynamic Scenes • Create a multi-view video dataset • Stereo video ➡️ 3D mask volume (disoccluded regions) ➡️ blend static/dynamic MPI. cseweb.ucsd.edu//~viscomp/pr…
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Announcing @ICCV_2021 workshop on "Unsupervised 3D Learning in the Wild" with an incredible line-up of speakers on this topic! #ICCV2021 🚩 Website: unsup3d.github.io 📅 Time: 7:00-18:00 EDT / 12:00-23:00 BST, 11 Oct 2021 Calendar: calendar.google.com/calendar… (mark it down!)
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Libing Zeng retweeted
Mind-blowing work
StyleNeRF: A Style-based 3D Aware Generator for High-resolution Image Synthesis abs: openreview.net/forum?id=iUuz… a 3D-aware generative model that can synthesize high-resolution images with high multi-view consistency
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Libing Zeng retweeted
TöRF: Time-of-Flight Radiance Fields for Dynamic Scene View Synthesis pdf: arxiv.org/pdf/2109.15271.pdf abs: arxiv.org/abs/2109.15271 project page: imaging.cs.cmu.edu/torf/
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