Loading video...

Video Failed to Load

There was a problem loading this video. This could be due to a temporary network issue or the video might be unavailable.

SpatialTrackerV2: unified, end-to-end 3D point tracking model which simultaneously estimates Camera Motion, Consistent Geometry and Pixel-wise 3D Trajectories.

Bilawal Sidhu

103,911 subscribers

20,346 views • 10 months ago •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

4 Comments

Bilawal Sidhu10 months ago

New ICCV paper. Here's a HuggingFace demo you can try today, as well as code for the offline tracker. Full paper and code release forthcoming.

Prashant10 months ago

spatial ai is so important for building the digiverse

Himanshu Kumar10 months ago

Impressive, but true spatial awareness needs object permanence, not just point tracking.

Zoe Ai collab manager10 months ago

Dm

Related Videos

Introducing FLARE #CVPR2026 2025 FLARE is a feed-forward model that simultaneously estimates high-quality camera poses, 3D geometry, and appearance from sparse uncalibrated images. 1/4

Introducing FLARE #CVPR2026 2025 FLARE is a feed-forward model that simultaneously estimates high-quality camera poses, 3D geometry, and appearance from sparse uncalibrated images. 1/4

Gordon Wetzstein

29,518 views • 1 year ago

We present VLM-3R: a Vision-Language Model capable of 3D spatial reasoning from monocular video, grounding visual cues, geometry, and camera motion. ✅ No depth sensor ✅ No pre-built 3D maps ✅ End-to-end spatial + temporal reasoning 🔗 Code & benchmark: #VLM #3DVision #LLMs

We present VLM-3R: a Vision-Language Model capable of 3D spatial reasoning from monocular video, grounding visual cues, geometry, and camera motion. ✅ No depth sensor ✅ No pre-built 3D maps ✅ End-to-end spatial + temporal reasoning 🔗 Code & benchmark: #VLM #3DVision #LLMs

Zhiwen(Aaron) Fan

14,895 views • 1 year ago

"YoNoSplat: You Only Need One Model for Feedforward 3D Gaussian Splatting" TL;DR: a unified 3D Gaussian splatting model that reconstructs high-quality scene geometry and camera poses from unposed/uncalibrated images in a single forward pass.

"YoNoSplat: You Only Need One Model for Feedforward 3D Gaussian Splatting" TL;DR: a unified 3D Gaussian splatting model that reconstructs high-quality scene geometry and camera poses from unposed/uncalibrated images in a single forward pass.

Alexandre Morgand

14,839 views • 3 months ago

RTFM can be seen as a learned renderer: it is an autoregressive diffusion transformer trained end-to-end on large-scale video data, and it learns to model 3D geometry, reflections, shadows and more just by observing them in its training set.

RTFM can be seen as a learned renderer: it is an autoregressive diffusion transformer trained end-to-end on large-scale video data, and it learns to model 3D geometry, reflections, shadows and more just by observing them in its training set.

World Labs

15,870 views • 7 months ago

i bought a iphone just to add tracking to my model 💀 2d live pixel texture face on a 3d body made in the #GodotEngine

i bought a iphone just to add tracking to my model 💀 2d live pixel texture face on a 3d body made in the #GodotEngine

byte 🕹️ nme64 | DEBUT: TBA

50,930 views • 2 years ago

Crazy 3D Model VTuber Tracking 🥴

Crazy 3D Model VTuber Tracking 🥴

Auteru🐣🌟

12,702 views • 1 year ago

Christian Rupprecht explains their interpretability research in 3D computer vision, testing if (and where in the model) multi-view transformers like VGGT, DepthAnything 3, and DUSt3R use point/patch correspondences to make sense of 3D scene geometry.

Christian Rupprecht explains their interpretability research in 3D computer vision, testing if (and where in the model) multi-view transformers like VGGT, DepthAnything 3, and DUSt3R use point/patch correspondences to make sense of 3D scene geometry.

Chris Offner

73,983 views • 2 months ago

Created #GameChanger 3D Motion Teaser !! Do Watch Till the End 🫶♥️ !!

Created #GameChanger 3D Motion Teaser !! Do Watch Till the End 🫶♥️ !!

சிறுத்தை

109,236 views • 1 year ago

Love these old meets new vfx workflows 1. extract a still of the object you want to augment 2. use image-to-3d to make a 3d model of the object 3. use that 3d geometry for classical object tracking Then you can go wild with complete control

Love these old meets new vfx workflows 1. extract a still of the object you want to augment 2. use image-to-3d to make a 3d model of the object 3. use that 3d geometry for classical object tracking Then you can go wild with complete control

Bilawal Sidhu

33,824 views • 1 year ago

Champ Controllable and Consistent Human Image Animation with 3D Parametric Guidance In this study, we introduce a methodology for human image animation by leveraging a 3D human parametric model within a latent diffusion framework to enhance shape alignment and motion

Champ Controllable and Consistent Human Image Animation with 3D Parametric Guidance In this study, we introduce a methodology for human image animation by leveraging a 3D human parametric model within a latent diffusion framework to enhance shape alignment and motion

AK

194,356 views • 2 years ago

3D-R1 is out on Hugging Face Enhancing Reasoning in 3D VLMs for Unified Scene Understanding 3D-R1 is an open-source generalist model that enhances the reasoning of 3D VLMs for unified scene understanding

3D-R1 is out on Hugging Face Enhancing Reasoning in 3D VLMs for Unified Scene Understanding 3D-R1 is an open-source generalist model that enhances the reasoning of 3D VLMs for unified scene understanding

AK

34,729 views • 10 months ago

byebye expensive motion tracking equipment 👋 ai makes motion capturing so easy now! nvidia presented GENMO last week, a new model that can generate and estimate human motion from text, audio, video, and 3D keyframes

byebye expensive motion tracking equipment 👋 ai makes motion capturing so easy now! nvidia presented GENMO last week, a new model that can generate and estimate human motion from text, audio, video, and 3D keyframes

Dreaming Tulpa 🥓👑

73,693 views • 1 year ago

Most generative models predict pixels. Predicting a 3D scene instead has many benefits: the scene won’t change if you look away and come back, and it obeys the basic physical rules of 3D geometry. The simplest way to visualize the 3D scene is a depth map, where each pixel is colored by its distance to the camera. 4/n

Most generative models predict pixels. Predicting a 3D scene instead has many benefits: the scene won’t change if you look away and come back, and it obeys the basic physical rules of 3D geometry. The simplest way to visualize the 3D scene is a depth map, where each pixel is colored by its distance to the camera. 4/n

World Labs

16,605 views • 1 year ago

🪬 #Live3D #Live2D #Live2DWIP 🪬 Testing finger articulation... Left: randomized auto motion Right: real-time camera tracking I wonder how many Vtubers would consider adding this kind of pseudo-3D hand to their Live2D model 🧐?

🪬 #Live3D #Live2D #Live2DWIP 🪬 Testing finger articulation... Left: randomized auto motion Right: real-time camera tracking I wonder how many Vtubers would consider adding this kind of pseudo-3D hand to their Live2D model 🧐?

📐Hephaestus📏Live2D匠人魂

36,072 views • 4 months ago

🚨 Pixal3D is now live on fal! 🧊 High-fidelity 3D assets from a single image 🎯 Pixel-aligned back-projection for direct pixel-to-3D correspondence 🎨 Detailed geometry with PBR textures, ready for downstream pipelines

🚨 Pixal3D is now live on fal! 🧊 High-fidelity 3D assets from a single image 🎯 Pixel-aligned back-projection for direct pixel-to-3D correspondence 🎨 Detailed geometry with PBR textures, ready for downstream pipelines

fal

14,192 views • 24 days ago

Introducing Texel Splatting: Perspective-Stable 3D Pixel Art open source paper+code Most 3D pixel art techniques (e.g. t3ssel8r, ProPixelizer) snap pixels to a screen grid, which only works with an orthographic camera Texel splatting solves this for perspective cameras: first,

Introducing Texel Splatting: Perspective-Stable 3D Pixel Art open source paper+code Most 3D pixel art techniques (e.g. t3ssel8r, ProPixelizer) snap pixels to a screen grid, which only works with an orthographic camera Texel splatting solves this for perspective cameras: first,

dylan

111,188 views • 2 months ago

Supervised learning has held 3D Vision back for too long. Meet RayZer — a self-supervised 3D model trained with zero 3D labels: ❌ No supervision of camera & geometry ✅ Just RGB images And the wild part? RayZer outperforms supervised methods (as 3D labels from COLMAP is noisy) 🌐 Project: (1/4)

Supervised learning has held 3D Vision back for too long. Meet RayZer — a self-supervised 3D model trained with zero 3D labels: ❌ No supervision of camera & geometry ✅ Just RGB images And the wild part? RayZer outperforms supervised methods (as 3D labels from COLMAP is noisy) 🌐 Project: (1/4)

Hanwen Jiang

69,460 views • 1 year ago

3D controllable video generation works well now and pixel alignment is impressive! We took our new 3D sculpt model, generated a blender scene and then asked a video-to-video model to render. Image to 3D sculpt: Common Sense Machines Synthetic rendering: Blender 🔶 Video-to-Video: Runway

3D controllable video generation works well now and pixel alignment is impressive! We took our new 3D sculpt model, generated a blender scene and then asked a video-to-video model to render. Image to 3D sculpt: Common Sense Machines Synthetic rendering: Blender 🔶 Video-to-Video: Runway

Common Sense Machines

18,714 views • 1 year ago