Video yükleniyor...

Video Yüklenemedi

Ana Sayfaya Dön

Learn how to combine a deep learning model for pose estimation to perform a 3D reconstruction using two cameras 📸

MATLAB's profile picture

MATLAB

102,559 subscribers

15,665 görüntüleme • 1 yıl önce •via X (Twitter)

Bilim & TeknolojiEğitimSanat
LIVE

Anya Rossi• Live Now

Private livecam show

0 Yorum

Yorum bulunmuyor

Orijinal gönderinin yorumları burada görünecek

Benzer Videolar

hi all, excited to join! i'm building an expressive mini "shoggoth" robot which will eventually be hooked up to gpt4o realtime voice. i'm currently working on the low-level policies, which are trained in a mujoco simulation with RL. to delay working on raw-pixels for now, i trained a pose-estimation model using deeplabcut and triangulate the position in 3d space using the stereo cameras. eventually, i'll use gpt4o's tool calling capabilities to activate several of these policies (closed and open loop) based on the dialog flow! captions: manual actuation of the tentacle / 3d pose estimation / target design
0:29

hi all, excited to join! i'm building an expressive mini "shoggoth" robot which will eventually be hooked up to gpt4o realtime voice. i'm currently working on the low-level policies, which are trained in a mujoco simulation with RL. to delay working on raw-pixels for now, i trained a pose-estimation model using deeplabcut and triangulate the position in 3d space using the stereo cameras. eventually, i'll use gpt4o's tool calling capabilities to activate several of these policies (closed and open loop) based on the dialog flow! captions: manual actuation of the tentacle / 3d pose estimation / target design

Matthieu LC

45,506 görüntüleme • 1 yıl önce

How can we use test-time compute for spatial understanding? 🤔 In InterPose, we propose to repeatedly sample generative video models to help two-view pose estimation and reconstruction, by leveraging the video models' keyframe interpolation abilities. A 🧵... (1/8)
0:17

How can we use test-time compute for spatial understanding? 🤔 In InterPose, we propose to repeatedly sample generative video models to help two-view pose estimation and reconstruction, by leveraging the video models' keyframe interpolation abilities. A 🧵... (1/8)

Ricardo Martin-Brualla

21,685 görüntüleme • 1 yıl önce

I've started reading Dungeon Meshi and also been doing a lot of 2D/3D mixed stuff in Blender recently, so of course I had to combine the two. Had a lot of fun learning how to combine vertex painting with pixel textures for this one. #dungeonmeshi #pixelart #Blender3d
0:16

I've started reading Dungeon Meshi and also been doing a lot of 2D/3D mixed stuff in Blender recently, so of course I had to combine the two. Had a lot of fun learning how to combine vertex painting with pixel textures for this one. #dungeonmeshi #pixelart #Blender3d

Paul Veer

279,458 görüntüleme • 3 yıl önce

Monocular pose estimation has gotten really good Grab any 2D video and transfer the performance to a 3D character
0:11

Monocular pose estimation has gotten really good Grab any 2D video and transfer the performance to a 3D character

Bilawal Sidhu

27,074 görüntüleme • 1 yıl önce

Try new poses and angles! 3D drawing figures are ideal for when you have a pose in mind but can't find that perfect reference image. Learn how to apply poses and other fun additions like BVH files to your 3D model in this tutorial: #clipstudio
0:16

Try new poses and angles! 3D drawing figures are ideal for when you have a pose in mind but can't find that perfect reference image. Learn how to apply poses and other fun additions like BVH files to your 3D model in this tutorial: #clipstudio

CLIP STUDIO PAINT

165,643 görüntüleme • 11 ay önce

ViTPose -- best open-source pose estimation model just landed to Hugging Face transformers 🕺🏻💃🏻 See how to use on the next one ⤵️
0:10

ViTPose -- best open-source pose estimation model just landed to Hugging Face transformers 🕺🏻💃🏻 See how to use on the next one ⤵️

merve

83,367 görüntüleme • 1 yıl önce

Discover the right 3D Geometric Foundation Model for your task—whether it’s stereo matching, multi-view depth estimation, video depth, pose estimation, semantic understanding, or novel view synthesis. Explore more insights in our #E3DBench #FoundationModel #3D #GaussianSplatting. Project Webpage:
0:14

Discover the right 3D Geometric Foundation Model for your task—whether it’s stereo matching, multi-view depth estimation, video depth, pose estimation, semantic understanding, or novel view synthesis. Explore more insights in our #E3DBench #FoundationModel #3D #GaussianSplatting. Project Webpage:

Zhiwen(Aaron) Fan

29,920 görüntüleme • 1 yıl önce

Created a quick VFX to make Wimbledon more green🌱 Using Camera Pose Estimation, body & ball segmentation to incorporate the grass simulation 🙂
0:12

Created a quick VFX to make Wimbledon more green🌱 Using Camera Pose Estimation, body & ball segmentation to incorporate the grass simulation 🙂

Alexandre Devaux

19,557 görüntüleme • 11 ay önce

I always thought camera pose estimation is necessary for 3D reconstruction, until Zequn and Stephen proved me wrong! Introducing PreF3R, purely feed-forward 3D Gaussian Splatting without any intermediate pose estimation and COLMAP initialization. Video in, 3D Gaussians and novel view rendering out. Key technique: spatial memory network from Spann3R and Gaussian head supervised by pointmap loss plus photometric loss. See more at:
0:19

I always thought camera pose estimation is necessary for 3D reconstruction, until Zequn and Stephen proved me wrong! Introducing PreF3R, purely feed-forward 3D Gaussian Splatting without any intermediate pose estimation and COLMAP initialization. Video in, 3D Gaussians and novel view rendering out. Key technique: spatial memory network from Spann3R and Gaussian head supervised by pointmap loss plus photometric loss. See more at:

Heng Yang

20,160 görüntüleme • 1 yıl önce

random model find; might be the best 3D multi-person pose estimation I have ever seen; it's Apache-2.0 Multi-HMR: Regressing Whole-Body Human Meshes for Multiple Persons in a Single Shot; ECCV2024
0:17

random model find; might be the best 3D multi-person pose estimation I have ever seen; it's Apache-2.0 Multi-HMR: Regressing Whole-Body Human Meshes for Multiple Persons in a Single Shot; ECCV2024

SkalskiP

31,150 görüntüleme • 1 yıl önce

Ever had a perfect image in mind that a text-to-image model just couldn't capture? Our new reinforcement learning agent, PASTA, turns image generation into a collaborative conversation, learning your style to bring your vision to life. Learn how it works:
0:19

Ever had a perfect image in mind that a text-to-image model just couldn't capture? Our new reinforcement learning agent, PASTA, turns image generation into a collaborative conversation, learning your style to bring your vision to life. Learn how it works:

Google Research

25,808 görüntüleme • 8 ay önce

Create a 3D model from a single image, set of images or a text prompt in < 1 minute 😮‍💨 This new AI paper called CAT3D shows us that it’ll keep getting easier to produce 3D models from 2D images — whether it’s a sparser real world 3D scan (a few photos instead of hundreds) or your favorite 2D image generator like Midjourney (just an image). How does this magic work? “This architecture is similar to video diffusion models, but with camera pose embeddings for each image instead of time embeddings. The generated views are passed into a robust 3D reconstruction pipeline to create the 3D representation (Zip-NeRF or 3DGS)”
0:18

Create a 3D model from a single image, set of images or a text prompt in < 1 minute 😮‍💨 This new AI paper called CAT3D shows us that it’ll keep getting easier to produce 3D models from 2D images — whether it’s a sparser real world 3D scan (a few photos instead of hundreds) or your favorite 2D image generator like Midjourney (just an image). How does this magic work? “This architecture is similar to video diffusion models, but with camera pose embeddings for each image instead of time embeddings. The generated views are passed into a robust 3D reconstruction pipeline to create the 3D representation (Zip-NeRF or 3DGS)”

Bilawal Sidhu

92,760 görüntüleme • 2 yıl önce

🌿 Introducing pesto~ for Max/MSP! A standalone wrapper for real-time neural pitch estimation powered by Sony CSL's PESTO deep learning model. Get robust, timbre-agnostic, low-latency (&lt;5ms) pitch tracking with confidence &amp; amplitude outputs in your Max patches.
0:17

🌿 Introducing pesto~ for Max/MSP! A standalone wrapper for real-time neural pitch estimation powered by Sony CSL's PESTO deep learning model. Get robust, timbre-agnostic, low-latency (&lt;5ms) pitch tracking with confidence &amp; amplitude outputs in your Max patches.

Qosmo — AI Creativity & Music Lab

16,822 görüntüleme • 1 yıl önce

Recently, I've been working a lot on Gaussian Splatting. I built a repo for camera pose estimation using Rerun, Gradio, and prefix.dev that merges GLOMAP with hloc! 🧵More info below
0:18

Recently, I've been working a lot on Gaussian Splatting. I built a repo for camera pose estimation using Rerun, Gradio, and prefix.dev that merges GLOMAP with hloc! 🧵More info below

Pablo Vela

67,547 görüntüleme • 1 yıl önce

pretty confident in the model being done now, all thats left is rigging! learning how to set up a proper foot roll for this model
0:16

pretty confident in the model being done now, all thats left is rigging! learning how to set up a proper foot roll for this model

LogiBob

26,744 görüntüleme • 5 ay önce

Tips &amp; Teach How To Pose 😍📸
0:19

Tips &amp; Teach How To Pose 😍📸

Photography 📸 Tips & Trick

103,655 görüntüleme • 2 yıl önce

Detect worker falls in real time with Ultralytics YOLO26! 📦 Combine object detection and pose estimation to identify when a person carrying luggage boxes falls, helping logistics teams improve warehouse safety and respond faster to incidents. Get started ➡️ #Ultralytics #YOLO26 #AI #Logistics #WorkplaceSafety
0:18

Detect worker falls in real time with Ultralytics YOLO26! 📦 Combine object detection and pose estimation to identify when a person carrying luggage boxes falls, helping logistics teams improve warehouse safety and respond faster to incidents. Get started ➡️ #Ultralytics #YOLO26 #AI #Logistics #WorkplaceSafety

Ultralytics

15,927 görüntüleme • 1 ay önce

A lot of people mistake the frog pose to dog pose Watch and learn
0:14

A lot of people mistake the frog pose to dog pose Watch and learn

BERNARDO 🏴‍☠️

38,991 görüntüleme • 4 ay önce

📢We introduce “RefFusion”, a novel inpainting method for scenes reconstructed using 3D Gaussian Splatting. 🔗 TLDR: we personalize an image diffusion model to a given reference image and distill its knowledge to 3D through score distillation sampling.
0:11

📢We introduce “RefFusion”, a novel inpainting method for scenes reconstructed using 3D Gaussian Splatting. 🔗 TLDR: we personalize an image diffusion model to a given reference image and distill its knowledge to 3D through score distillation sampling.

Ashkan Mirzaei

34,683 görüntüleme • 2 yıl önce