Fuji Tsang Clément

177 posts

Fuji Tsang Clément

Fuji Tsang Clément

@Caenorst

AI Enthusiast, Research Scientist at NVIDIA

US / FR / CA เข้าร่วม Ağustos 2012
175 กำลังติดตาม148 ผู้ติดตาม
Fuji Tsang Clément รีทวีตแล้ว
NVIDIA AI Developer
NVIDIA AI Developer@NVIDIAAIDev·
Most 3DGS segmentation tools either pre‑train per scene or lock errors into a feature field you can’t undo. ArtisanGS instead turns a few 2D masks into editable 3D object selections via Cutie tracking + black‑box splat aggregation, then lets you iteratively correct mistakes with consistent 2D/3D selection modes. 📗 #NVIDIAResearch paper: arxiv.org/abs/2602.10173
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Fuji Tsang Clément
Fuji Tsang Clément@Caenorst·
@VFSGlobal @vfsglobalcare Can you please try to fix your website? I've been trying to apply for Visa for France for my relatives to attend my wedding for a month now and it's always crashing...
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Fuji Tsang Clément
Fuji Tsang Clément@Caenorst·
So proud of the Kaolin team with our new release, join our Hands-on lab at #SIGGRAPH2024 to learn how Kaolin can improve your 3D Deep Learning workflow and enable interactive physics in your Jupyter notebook! s2024.conference-program.org/presentation/?…
NVIDIA AI Developer@NVIDIAAIDev

✨Just announced: Representation agnostics physics simulation. ➡️ nvda.ws/3SuHUXZ This new framework is now available in the Kaolin Library. Simulate: ✅Gaussian Splats ✅Neural Radiance Fields ✅Signed Distance Functions and more…

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Fuji Tsang Clément รีทวีตแล้ว
NVIDIA AI Developer
NVIDIA AI Developer@NVIDIAAIDev·
✨Just announced: Representation agnostics physics simulation. ➡️ nvda.ws/3SuHUXZ This new framework is now available in the Kaolin Library. Simulate: ✅Gaussian Splats ✅Neural Radiance Fields ✅Signed Distance Functions and more…
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Jonathan Lorraine
Jonathan Lorraine@jonLorraine9·
Thrilled to announce I've completed my PhD! 🎉 My advisor, @DavidDuvenaud's support and guidance made the journey enjoyable. You showed me that research can be fun, and I will always cherish our brainstorming sessions on the whiteboard. Thank you for taking a chance on me and for your never-ending support, even during the more disappointing paper rejections. I'll always fondly look back on my times in grad school.
Jonathan Lorraine tweet media
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Fuji Tsang Clément รีทวีตแล้ว
NVIDIA AI Developer
NVIDIA AI Developer@NVIDIAAIDev·
Exciting news for #PyTorch enthusiasts: Our NVIDIA Kaolin library introduces SurfaceMesh class to simplify managing mesh attributes including consistency, auto-compute normals, & streamline indexing. 👀 See the video tutorial from #NVIDIAResearch ➡️ nvda.ws/4aRCi1D
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Fuji Tsang Clément
Fuji Tsang Clément@Caenorst·
@JulieChangRE The article says "the middle 20 percent of income" and the bottom income is not the same as the top income of the bottom 20%. So there is a whole range of income missing (between $56,000 and $617,900 !!! and between $23,200 and $35,800)
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Julie Chang
Julie Chang@JulieChangRE·
“Texans actually pay more in taxes than Californians do, unless those Texans are in the top one percent of all earners. “ chron.com/news/houston-t…
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Fuji Tsang Clément รีทวีตแล้ว
Masha Shugrina
Masha Shugrina@_shumash·
If you want to visualize 3D Gaussian Splatting radiance fields *interactively* in a Jupyter Notebook, here's an easy recipe using Kaolin Library: youtube.com/watch?v=OcvA7f…
YouTube video
YouTube
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Fuji Tsang Clément
Fuji Tsang Clément@Caenorst·
Excited about this new release, the interactive visualizer and SurfaceMesh class are strong improvements of QoL when debugging a renderer or a model. Great job from the team @_shumash @OrPerel @FidlerSanja @NVIDIAAI
NVIDIA AI Developer@NVIDIAAIDev

📣 Just released: #NVIDIAKaolin v0.14.0 Accelerate 3D deep learning research, debug your custom renderer interactively in a Jupyter notebook, and manage batched mesh attributes with a SurfaceMesh container, within the Kaolin #Pytorch library. Github: nvda.ws/3QeuDCr

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Fuji Tsang Clément
Fuji Tsang Clément@Caenorst·
Super excited about this release, Kaolin is now installable with a single command line! Check out our tutorials on lighting: Diffuse: github.com/NVIDIAGameWork… Specular: github.com/NVIDIAGameWork… Documentation: kaolin.readthedocs.io/en/latest/modu…
NVIDIA AI Developer@NVIDIAAIDev

📣 Just released: #NVIDIAKaolin v0.13.0 With new lighting features enabling #3D DL works like DIBR++ or NeRD, check out our tutorials on diffuse and specular reflectance. Kaolin is now pip installable. Installation: nvda.ws/3YN40FY Release notes: nvda.ws/3EbEYZ2

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Fuji Tsang Clément
Fuji Tsang Clément@Caenorst·
@RanaHanocka That can actually be very useful to generate test cases for 3D functions! I’ll definitely give it a try.
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Rana Hanocka
Rana Hanocka@RanaHanocka·
Here is the chatgpt response. Chatgpt seems to be able to generate .objs for simple stuff, but the geometry starts to break down for more complicated requests. Still, I think this shows promise for a 3D model creation through a natural conversation! 2/
Rana Hanocka tweet mediaRana Hanocka tweet media
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Rana Hanocka
Rana Hanocka@RanaHanocka·
I asked chatgpt to generate an .obj file of a tetrahedron. It generated a list of vertices/faces in the .obj format. If you paste that into an empty file, it will open up in a 3D viewer, like meshlab! (It's even topologically correct: manifold, correct face normals, etc) 1/
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Fuji Tsang Clément
Fuji Tsang Clément@Caenorst·
@srush_nlp @davidweichiang @boazbaraktcs One of the big advantage of named tensor is to allow flexibility for the compiler / JIT to make optimization in the backend without having any intervention from user, an example is the painful transition from NCHW to NHWC for convolution on recent GPU
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Fuji Tsang Clément
Fuji Tsang Clément@Caenorst·
@fhuszar Hehe, good espresso at home take some time and skills (and money), especially if you like those light roast goodness
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Ferenc Huszár
Ferenc Huszár@fhuszar·
How it started — how it’s going.
Ferenc Huszár tweet mediaFerenc Huszár tweet media
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Fuji Tsang Clément รีทวีตแล้ว
Or Perel
Or Perel@OrPerel·
New demo for wisp! Kaolin's Structured Point Clouds (SPCs) can now be traced within the interactive visualizer. SPCs can be converted from meshes, quantized point clouds and sparse voxel grids. Check it out here: github.com/NVIDIAGameWork… #NVIDIAKaolinWisp #Nvidia #neuralfields
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Fuji Tsang Clément
Fuji Tsang Clément@Caenorst·
@wojczarnecki @francoisfleuret @PyTorch Well, broadcasting operations are way more efficient than the element-wise alternative. You can "expand" to have a similar effect to broadcasting (unless you use "contiguous()") but lots of researchers would use "repeat" without knowing that it doesn't behave the same.
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Wojciech Czarnecki
Wojciech Czarnecki@wojczarnecki·
@francoisfleuret @PyTorch I have the same feeling about forbidding all the DL libraries from implementing auto broadcasting. Just... Don't. Vector plus vector should never result in a matrix......
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François Fleuret
François Fleuret@francoisfleuret·
If @PyTorch was printing the sizes, dtype and devices of all the tensors involved in an operation that failed, we would be getting AGI ten years earlier.
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Fuji Tsang Clément รีทวีตแล้ว
Jun Gao
Jun Gao@JunGao33210520·
Excited to share our #NeurIPS2022 @NVIDIAAI work GET3D, a generative model that directly produces explicit textured 3D meshes with complex topology, rich geometric details, and high fidelity textures. #3D Project page: nv-tlabs.github.io/GET3D/
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ค้นพบ

@VFSGlobal @vfsglobalcare @jonLorraine9 @DavidDuvenaud @JulieChangRE @_shumash @OrPerel @FidlerSanja