I occasionally post AI memes.
yashbhalgat.github.io
Topics: 3D-VLA models, LLM agents for 3D scene understanding, Robotic control with language.
📢 Call for papers: Deadline – April 20, 2025
🌐 Details: 3d-llm-vla.github.io
#llm #3d #Robotics #ai
Topics: 3D-VLA models, LLM agents for 3D scene understanding, Robotic control with language.
📢 Call for papers: Deadline – April 20, 2025
🌐 Details: 3d-llm-vla.github.io
#llm #3d #Robotics #ai
@bernhard-jaeger.bsky.social
www.nowpublishers.com/article/Deta...
arxiv.org/abs/2312.08365
@bernhard-jaeger.bsky.social
www.nowpublishers.com/article/Deta...
arxiv.org/abs/2312.08365
New work from UCSD and Adobe:
"RigAnything: Template-Free Autoregressive Rigging
for Diverse 3D Assets" Liu et al.
tl;dr: reduces rigging time from 2 mins to 2 secs, works on any shape category & doesn't need predefined templates! 🚀
New work from UCSD and Adobe:
"RigAnything: Template-Free Autoregressive Rigging
for Diverse 3D Assets" Liu et al.
tl;dr: reduces rigging time from 2 mins to 2 secs, works on any shape category & doesn't need predefined templates! 🚀
tl;dr: Novel framework that integrates 3D awareness into VAE latent space using correspondence-aware encoding, enabling high-quality rendered images with ~50% memory savings.
(1/n) 🧵
tl;dr: Novel framework that integrates 3D awareness into VAE latent space using correspondence-aware encoding, enabling high-quality rendered images with ~50% memory savings.
(1/n) 🧵
Their mesh tokenization algorithm (adapted from EdgeBreaker) achieves ~50% compression (4-5 tokens per face vs 9), making training efficient.
Their mesh tokenization algorithm (adapted from EdgeBreaker) achieves ~50% compression (4-5 tokens per face vs 9), making training efficient.
Code available (pretrained models too) 🤩: github.com/wyysf-98/Cra...
(1/n) 🧵
Code available (pretrained models too) 🤩: github.com/wyysf-98/Cra...
(1/n) 🧵
"GSLoc: Efficient Camera Pose Refinement via 3D Gaussian Splatting"
TL;DR: a novel test-time camera pose refinement framework leveraging 3DGS as the scene representation and MASt3R for 2D matching.
🔗: arxiv.org/abs/2408.11085
"GSLoc: Efficient Camera Pose Refinement via 3D Gaussian Splatting"
TL;DR: a novel test-time camera pose refinement framework leveraging 3DGS as the scene representation and MASt3R for 2D matching.
🔗: arxiv.org/abs/2408.11085
Swiss startup Sun-ways will run a pilot project turning train lines into clean energy highways.
#renewable #energy for the win 🤓
www.pv-magazine.com/2024/10/04/s...
Swiss startup Sun-ways will run a pilot project turning train lines into clean energy highways.
#renewable #energy for the win 🤓
www.pv-magazine.com/2024/10/04/s...
www.pv-magazine.com/2024/10/04/s...
www.pv-magazine.com/2024/10/04/s...
Please re-post!
Note: Oxford recruits faculty at Associate Professor level - we have no Assistant Professor level.
Recruiting for 3 Information Engineering faculty - including Robotics, Computer Vision, Machine Learning. Please repost!
Faculty positions in Oxford are typically linked to a college.
⬇️ details in thread ⬇️
Please re-post!
Note: Oxford recruits faculty at Associate Professor level - we have no Assistant Professor level.
Cool stuff! Let's you visualize each operation or layer in different Transformer architectures, and also explains them on the side. 😍
#llm #visualisation #gpt #ai #transformers
Cool stuff! Let's you visualize each operation or layer in different Transformer architectures, and also explains them on the side. 😍
#llm #visualisation #gpt #ai #transformers
(1/2) Encodes SVGs as implicit neural representations using a small MLP trained with Score Distillation Sampling (SDS). Maps 2D coordinates to shape/color outputs. Dropout-like technique ensures ordered, layered structures.
(1/2) Encodes SVGs as implicit neural representations using a small MLP trained with Score Distillation Sampling (SDS). Maps 2D coordinates to shape/color outputs. Dropout-like technique ensures ordered, layered structures.
A differentiable rendering framework for direct #exoplanet imaging, leveraging wavefront sensing to refine starlight subtraction. Tested on JWST, it approaches noise limits and reveals faint planets like never before! 🚀
#ai #astronomy
A differentiable rendering framework for direct #exoplanet imaging, leveraging wavefront sensing to refine starlight subtraction. Tested on JWST, it approaches noise limits and reveals faint planets like never before! 🚀
#ai #astronomy
🔗: github.com/yashbhalgat/...
#instantngp #neuralradiancefield #3d #computervision #research #python
🔗: github.com/yashbhalgat/...
#instantngp #neuralradiancefield #3d #computervision #research #python
Project page: val.cds.iisc.ac.in/reflecting-r...
Project page: val.cds.iisc.ac.in/reflecting-r...
We are accepting paper submissions on a range of topics. More details on the website: abdullahamdi.com/3dmv2024/
#computervision #ai
We are accepting paper submissions on a range of topics. More details on the website: abdullahamdi.com/3dmv2024/
#computervision #ai